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This article was originally published on CIO.com by Metis Strategy Partner Chris Davis, Managing Director Tony Qamar, and Senior Associate Grace Cozier.
CIOs are under pressure to deliver on AI’s promise. Yet history shows that many digital transformations have underdelivered — not because of strategy, process or technology, but because of people. Without engaged, enabled and aligned employees, even the most promising AI initiatives will stall. Models may be built, but they won’t be trusted or adopted. Workflows may be reengineered, but without buy-in, they’ll sit unused.
At Metis Strategy, our work alongside technology leaders, driving some of the world’s most complex transformations, has resoundingly taught us that success is always people first. The same lessons apply today as organizations pursue AI-powered transformations: those that succeed put people and culture at the center. Culture shapes every element of the operating model — what decisions are made, how decisions are made, how resources are prioritized and how quickly the company adapts.
Despite strong intentions and significant investments, many transformations falter because leaders misjudge where the true risks lie. A common failure pattern is over-indexing on technology or process while neglecting people. New AI platforms or workflows are often launched with great fanfare, but without engagement, enablement and alignment, employees struggle to adapt and value goes unrealized.
As the ADKAR framework highlights, sustainable change requires more than a solution — it requires awareness, desire, knowledge, ability and reinforcement at the individual level.
Another pitfall occurs when transformations become process exercises rather than engines of business value. When initiatives are framed as IT-only or designed around governance for its own sake, they lose relevance and fail to inspire the commitment needed for lasting change.
Transformations also stall when priorities are scattered or poorly communicated. Without enterprise-wide alignment, programs become optional, teams are spread too thin and execution suffers. In these cases, even well-designed AI strategies cannot deliver impact.
Finally, cultural resistance or a lack of trust can quietly derail transformations. Employees who do not see how AI initiatives align with their own incentives may disengage, breeding fatigue and undermining momentum. Without trust in data, models and leadership, adoption falters no matter how advanced the technology.
For CIOs, avoiding these patterns is essential. The organizations thriving in the AI era are those that design transformations with people and culture at the center from the very beginning. Through our client work, we’ve identified four cultural elements that consistently shape transformation outcomes — and four actions leaders can take today to strengthen them.
Successful transformations align operating models with customer needs. Too often, companies define themselves as “sales-led” or “product-led” and allow that orientation to drive key decisions. While this can create enterprise clarity, it risks sidelining customers or alienating parts of the organization.
In contrast, enterprises that adopt a true customer-first approach build resilience and agility across functions. Their operating models align incentives, prioritize experiences and ensure teams move in step with market needs. As explored in Achieving product success: A five-step framework for customer-centric design, an article written by Metis Strategy’s own Andre Lopes de Carvalho, organizations that embed customer centricity into their design and delivery processes create more value and are better equipped to sustain transformation.
Revisit your mission, values and incentive structures. Ensure they reinforce a culture where the customer is the anchor for decision-making at every level and for every department.
Digital and AI transformations are demanding. Employees must adapt to new ways of working, acquire new skills and deliver against rising expectations — all while managing day-to-day responsibilities. Without meaningful investment in people, fatigue and disengagement set in, jeopardizing transformation success and putting millions of dollars of investment at risk.
Leading organizations counter this by embedding continuous learning into their cultures. Targeted learning and development (L&D) programs, aligned with transformation priorities, not only upskill employees but also strengthen commitment to shared goals. The best programs address both business outcomes and personal growth — answering “what’s in it for me” alongside company goals.
Provide protected time and resources for development. Tie L&D investments directly to transformation outcomes to ensure employees are motivated and equipped to deliver. Acknowledge that meaningful learning requires space — even during working hours.
Leadership sets direction, but decision-making structures determine speed. Transformations falter under traditional command-and-control models, where approvals and escalations slow progress. The fewer people responsible for making decisions, the slower progress will be made.
Our experience shows that pushing decisions closer to the problem accelerates execution, improves accountability and fosters innovation. Empowered teams make better, faster choices — particularly when leaders set clear guardrails and reinforce trust. A decision-making framework, for example, clarifies which choices can be made locally and which warrant escalation, enabling faster, distributed decision-making.
Reduce layers of approval and empower small, cross-functional teams with decision rights. Ensure leadership behaviors reinforce empowerment, not control.
No transformation follows a straight path. Markets shift, technologies evolve and customer expectations change. AI adoption in particular requires experimentation — testing models, validating outcomes and adapting quickly to advances. Thriving organizations build cultures of experimentation where teams are encouraged to test, learn and adapt at speed.
We’ve seen this approach succeed when companies create the time and structure for experimentation, whether through dedicated capacity, lightweight governance or innovation programs. Not all experiments can succeed, so rather than penalizing failures, promote a culture that encourages learning from them. The result is not just innovation but resilience — a workforce confident in navigating uncertainty. As Jamie Engstrom emphasized in Technology, talent and transformation at caterpillar, curiosity and collaboration ensure experimentation is both grounded in business value and disciplined execution.
Normalize test-and-learn practices across teams. Protect capacity for experimentation, ensure lessons are shared and reward adaptability as much as execution.
Every transformation involves new strategies, processes and technologies. What ultimately determines success or failure is whether leaders place people and, by extension, culture, at the center. People shape decision-making, innovation and execution; they are the connective tissue of the operating model. CIOs who recognize culture as a true differentiator are better positioned to navigate complexity, make effective decisions and deliver sustained impact.
Wolters Kluwer’s ongoing transformation from a traditional publishing business to a cloud-first, AI-driven enterprise illustrates how people and culture drive successful AI-powered transformations. When we spoke with CIO Mark Sherwood, he discussed how customer centricity is reinforced through business relationship managers (BRM) who bridge technology and business units, ensuring digital investments are aligned with customer and market needs.
Learning and development are emphasized as employees build new skills in cloud, AI and data governance, enabling them to adapt to rapidly evolving technologies. Distributed decision-making is strengthened by embedding BRMs to bring tech and business closer together, ensuring alignment and enabling smarter choices on priorities and resources. Agility is fueled by a test-and-learn mindset, with experimentation balanced by strong ethical AI practices and disciplined measurement.
By maintaining a strong culture and people-first approach, Wolters Kluwer has accelerated its evolution and positioned itself as a leader in delivering trusted, technology-enabled solutions across industries.
CIOs today face constant change — none more urgent than the rise of AI. Shifting customer expectations, new competitive threats and accelerating disruptions are magnified in the AI era. Anchoring transformation in people and culture is what turns volatility into opportunity and lasting advantage.
For CIOs, the mandate is clear: build operating models that not only work today but also adapt continuously for tomorrow. That requires embedding four cultural practices at the center of every digital and AI transformation:
When CIOs champion these actions, they move beyond technology deployment to transformation that is embraced, scaled and sustained. Put people first and digital and AI transformations become not only achievable, but sustainable.
This article was originally published on CIO.com by Metis Strategy Partner Michael Bertha.
The days of treating corporate and digital strategy as separate entities are over since their convergence has become central to data-driven transformation. Yet very few companies believe in it strongly enough to restructure themselves around that reality.
“Investments and behaviors follow org design,” says Sandeep Davé, CBRE’s chief knowledge officer. “In the era of AI, the world requires integration, not isolation.”
For Davé, becoming chief knowledge officer represents more than a role change. It reflects a deliberate reframing of how CBRE approaches technology, strategy, and data.
The company, which serves clients in more than 100 countries and offers services ranging from capital markets and leasing advisory to investment management, project management and facilities management, has long been strategy-led. By elevating Davé from CDTO into a newly created role that unites corporate strategy, research, and data with the overall technology direction, CBRE is signaling that these functions are inseparable in shaping the company’s future.
Davé points to three forces behind the move.
The first is scale and complexity. With our scale — the clients, asset classes, services, and global reach — CBRE needed a way to harness and translate its vast data assets into knowledge and insights. “If we can see every property we touch, and convert that data into knowledge and insights, we create a formidable competitive moat,” he says.
The second is AI as a differentiator. “The thing that distinguishes what you can do with AI is data,” he says. “If AI delivers the transformative impact it promises, then your data foundation, governance, and strategic alignment will determine your rate of success.”
The third is organizational maturity. After years of scaling cutting-edge technology across the business, including the latest AI offerings, CBRE now has the platforms, infrastructure, and cultural readiness to take a bold next step. Functions that once operated in isolation are being reshaped.
Research offers a clear example of that reshaping. “We’re elevating our global research function by streamlining processes and improving outcomes,” Davé says. “Now, by applying AI and automation, we’re increasing efficiency while also significantly enhancing the quality of our outputs.”
The unification of functions reinforces a central truth in broad technology and AI adoption that context is king. Without it, even the most advanced tools deliver limited results. When technology, research, and strategy move together, the impact can be transformative.
Evidence of that transformation is already visible at CBRE. In facilities management, predictive analytics now inform repair-versus-replace decisions, cut duplicate work orders, and optimize service delivery. And across the enterprise, more than 65,000 employees use Ellis AI, the firm’s gen AI platform, to access trusted data, generate insights, and automate routine tasks.
“Tools alone don’t bend the cost curve,” says Davé. “It’s important to understand the environment, intent, and nuances that shape intended outcomes. When we combine the richness of our data with the insight of our people and the discipline of strategy, AI stops being a showcase of use cases and becomes a driver of real market differentiation.”
CBRE’s establishment of this position, particularly under Davé, signals a deliberate strategic move that says consolidating key functions under one remit is more purposeful and productive.
Conway’s Law is a useful reminder here whereby systems often mirror the communication patterns and structures of the organizations that build them. Fragmented companies and cultures yield fragmented technology solutions. For leaders serious about capturing the full value of AI, progress will demand more than governance frameworks or technology investments. It may require rethinking reporting lines, incentives, and collaboration models.
Convergence isn’t just an idea, it’s an operating model. And the future of AI-driven transformation will be shaped not only by the technology deployed, but how organizations choose to design themselves around it.
This article was originally published on Forbes by Peter High, President at Metis Strategy
When Glenn Remoreras joined Breakthru Beverage Group six months ago as Chief Information Officer, he stepped into a $8.6 billion revenue, family-owned enterprise with a deeply rooted legacy in the U.S. and Canadian beverage distribution industry. His mandate, however, is anything but traditional. Tasked with driving digital innovation, expanding a B2B e-commerce platform and raising AI literacy across the enterprise, Remoreras is on a mission to transform Breakthru into the most technologically advanced distributor in its class.
Driving Digital Commerce at Scale
Breakthru Beverage Group’s ambition to become the distributor of choice in its industry hinges on a strategic investment in digital commerce. At the heart of that transformation is Breakthru Now, a B2B e-commerce platform launched several years ago and recently accelerated under Remoreras’ leadership.
“Our target this year is $700 million of our revenue coming through this channel,” Remoreras noted with a note of excitement. “It really simplifies the customer experience in buying and transacting with us.” The company is also embedding AI and chatbots into the platform to enable dynamic recommendations and intelligent sales support, further enhancing the buyer journey.
But Remoreras sees digital commerce as only the starting point. “What I’m really excited about is reimagining our entire sales journey,” he underscored. “We’re a selling organization. A big portion of our 10,000-strong team is in sales. If you can modernize that end-to-end process, you differentiate. You become the most effective sales organization in the industry.”
Reinventing Sales with Co-Leadership and Technology
To modernize that journey, Remoreras has adopted a co-leadership model, tightly integrating technology with the commercial function. “This needs to be business-led,” he emphasized. “Our chief commercial officer and other stakeholders are thought partners. We examine where we are today and where tech can take us; or where it’s dragging us!”
He’s quick to admit that there are opportunities to modernize platform infrastructure. The aim is not only operational efficiency but enhanced field capabilities. “We have mobile and iPad tools in place, but we see room to reimagine,” he said. That reimagining includes preparing for the rise of agentic AI, intelligent systems capable of making decisions and learning over time. “When that technology matures, we want to be the first to deploy it meaningfully in our industry.”
Building the Foundation for AI: Data and Cloud
Remoreras’ AI vision is underpinned by a strong data and cloud foundation. “In the AI revolution, data is the fuel,” he said. “If you don’t have quality data or a modern architecture, you can’t achieve the flywheel effect that AI promises.”
To that end, Breakthru is partnering with AWS to migrate its compute environment to the cloud and enable scalable AI and ML experimentation. The company is also reshaping its data strategy and investing in internal data talent to retain intellectual property and create sustainable value. “It’s a fluid process,” he noted. “SAP, Salesforce, Snowflake—these partners are all evolving. We now have more optionality than ever.”
AI Literacy Before AI Use Cases
Rather than rushing to scale AI pilots, Remoreras is taking a more deliberate, education-first approach. In May, he organized an AI summit with CEO Tom Bené and the executive team, joined by over 20 senior leaders. Hosted at an Amazon distribution center and featuring five technology partners, the summit aimed to demystify AI’s potential.
“The goal was not to build use cases that day,” he said. “It was to leave the room more educated. When leadership is informed, they don’t come to you with a vague AI idea. They say, ‘I have a problem to solve. Can AI help?’”
That clarity is now sparking real exploration. Executives are surfacing problems—from customer engagement to marketing personalization—that AI might solve. With hackathons planned for the fall, Remoreras is curating a portfolio of value-driven use cases. “You don’t throw money at the hype,” he said. “You solve real problems. That’s how you scale.”
“You don’t throw money at the hype,” he said. “You solve real problems. That’s how you scale.”— Glenn Remoreras
“You don’t throw money at the hype,” he said. “You solve real problems. That’s how you scale.”
Innovation as a Team Sport
While the excitement around AI is palpable, Remoreras believes innovation must be embedded in the organizational structure. He favors a product-centric model with clearly defined business product owners partnered with IT leads in a “two-in-a-box” format.
“Each product has a long-term roadmap and backlog, supported by agile fusion teams,” he said. “That’s how innovation sticks. It’s business-led, tech-powered and supported by data services, cloud and cybersecurity.”
Breakthru is aligning these teams with strategic imperatives in areas like commercial effectiveness and operational excellence. “Innovation becomes repeatable when the structure supports it,” Remoreras said.
A Global Lens and Industry Perspective
Remoreras brings a rare blend of cross-industry and cross-cultural experience to his role. Having worked in beverage production with Constellation Brands and Mark Anthony Group, and now in distribution at Breakthru, he understands multiple layers of the industry’s three-tier system.
His earlier career at Cemex, where distribution, process and customer efficiency were core to success, informs his thinking today. “Where you win in distribution is different from where you win in brand manufacturing,” he explained. “The advantage I bring is a systems mindset and a network in the industry, but I draw just as much from outside experiences.”
As a native of the Philippines who has lived and worked across Asia, Europe, Mexico, Canada and the U.S., Remoreras credits global exposure with shaping his leadership philosophy. “Tech is the same everywhere; SAP, cloud, Microsoft. The difference is culture and people,” he said. “Resilience from the Philippines, precision from Germany, work ethic from Mexico, followership from Canada, agility from the U.S.; these all inform how I lead.”
Looking Ahead: Agentic AI and Purposeful Leadership
Looking toward the future, Remoreras is focused on the rapid emergence of agentic AI and its potential to redefine the workforce. “In 20 years, agentic AI will handle roles we now associate with people,” he said. “The shift is happening now, not in a decade.”
He’s personally invested in the transformation, even involving his 14-year-old twin sons in learning about AI. He’s also writing a book on AI slated for release in six months.
Despite the technological focus, Remoreras is grounded by purpose. A recent favorite read is The Earned Life by Marshall Goldsmith, which emphasizes presence and impact over mere success. “If I were financially set tomorrow, I’d be teaching at a community college,” he said. “But I’ve learned you can teach and inspire through your professional role.”
That philosophy has shaped everything from Breakthru’s AI literacy program to how he leads his team. “We do our best work, then go home and enjoy a glass of wine,” he said with a laugh. “That’s the balance I aim for.”
Peter High is President of Metis Strategy, a business and IT advisory firm. He has written three bestselling books, including his latest Getting to Nimble. He also moderates the Technovation podcast series and speaks at conferences around the world. Follow him on Twitter @PeterAHigh.
Shez Partovi is Chief Innovation and Strategy Officer and Chief Business Leader of Enterprise Informatics at Royal Philips, a global health technology company headquartered in the Netherlands. Philips is focused on improving health and well-being through meaningful innovation that combines advanced technology with deep clinical and consumer insight. In 2024, the company generated €18 billion in revenue and employs more than 67,000 people, serving customers in over 100 countries.
An experienced clinical professor, neuroradiologist, global executive and entrepreneur, Partovi brings a unique perspective shaped by decades of leadership in health systems, cloud transformation and artificial intelligence. Under his leadership, Philips is advancing its role as a trusted partner in integrated diagnostics, scaling analytics and driving workflow optimization across the healthcare continuum. Operating at the intersection of diagnostics, informatics and patient care, Partovi is helping to shape the company’s vision of delivering better care for more people, especially in an age marked by clinician shortages, cost pressures and exploding demand.
A Strategy Anchored in Customer Pain Points
Philips’ strategic approach is deceptively simple: invest in solving the customer’s problems, not in promoting the company’s ideas. “The best innovations are painkillers, not vitamins,” Partovi said, emphasizing a shift away from traditional R&D silos toward customer-driven design.
“The best innovations are painkillers, not vitamins.” — Shez Partovi
“The best innovations are painkillers, not vitamins.”
Each of Philips’ divisions, from precision diagnostics to sleep and respiratory care, applies this philosophy through formalized partnerships with health systems. These relationships often involve co-located teams of engineers, product managers and architects embedded directly in clinical environments. “We iterate at the bedside, in the radiology suite, or in the pathology lab,” Partovi explained. “That’s how we build algorithms, software and solutions that deliver meaningful outcomes.”
A standout example is the SmartSpeed AI software developed for Philips’ BlueSeal MRI scanners. Inspired by the needs of Leiden University Medical Center in the Netherlands, which faced a patient backlog, Philips built a neural network that tripled scan speeds and improved image resolution without requiring new hardware. “It’s a software-driven leap in productivity,” Partovi said. “And it came from listening to one customer’s pain point.”
Organizing Innovation for Scale
Innovation at Philips isn’t left to chance. Partovi oversees a tightly structured system that balances decentralization with long-horizon research. Roughly 80 percent of Philips’ R&D resources are embedded within its core business units, ensuring close proximity to customers and rapid feedback cycles. The remaining 20 percent reside in central innovation teams focused on industry-shifting breakthroughs.
A case in point is BlueSeal itself, which uses only seven liters of helium, far less than the industry-standard 1,500. “No one asked for helium-free MRI,” Partovi said. “But we saw sustainability and cost benefits years ago, and now the entire industry is moving in that direction.”
Whether close to market or looking around corners, all Philips innovation shares three traits: it must be
“We want to improve the lives of 2.5 billion people annually by 2030, including 400 million from underserved communities,” Partovi underscored. “That only happens if you build with global impact in mind.”
Reimagining Healthcare Software with Enterprise Informatics
Two years ago, Partovi expanded his responsibilities to include Philips’ Healthcare Informatics division. The move was strategic: unlike hardware, which has long product cycles, software must evolve continuously. “If an MRI scanner updates every two years, software should update every six weeks,” Partovi noted.
Philips consolidated its imaging and clinical informatics into a standalone unit to accelerate innovation. The division spans everything from diagnostic viewers for radiologists and pathologists to medical device integration that feeds predictive algorithms. “Inside a hospital, anything with a digital readout [including] ventilators, IV pumps, monitors, can ingest data and apply AI to it,” Partovi said.
These capabilities are already powering predictive solutions. At Massachusetts General Hospital in Boston, Philips is working to forecast respiratory distress in ICU patients, helping clinicians intervene earlier and improve outcomes.
Three Dimensions of AI: Automate, Augment, Agility
Partovi describes Philips’ AI strategy in terms of three functions: automation, augmentation and agility. Each serves to amplify clinical effectiveness and efficiency.
Partovi sees AI not as a replacement for caregivers but as a tool that expands capacity. “The most pressing challenge in healthcare is the gap between demand and supply,” he said. “AI helps us close that gap.”
Bridging the Trust Gap in AI
According to the latest Philips Future Health Index, a global survey of 16,000 patients and 2,000 clinicians, a notable gap persists between physician and patient trust in AI. While 79 percent of clinicians believe AI reduces burdens and improves care, only 59 percent of patients agree, and many worry AI might reduce time spent with doctors.
However, trust grows dramatically when humans remain in the loop. “Patients showed 86 percent confidence in AI when a physician was involved,” Partovi said. “The takeaway is clear: design AI to enhance, not replace, the human relationship.”
This insight has become central to Philips’ AI design philosophy, which stresses transparency, fairness and regulatory rigor. “Innovation must be responsible, or it’s not innovation at all,” Partovi emphasized.
Internal Use of Generative AI at Philips
While most attention goes to patient-facing applications, Philips is also leveraging AI internally across the enterprise. In software engineering, generative AI is now responsible for up to 30 percent of new code within some teams. “One developer told me, ‘I feel like I have a new job,’” Partovi recalled.
Customer service is also evolving. Large language models trained on Philips’ proprietary knowledge base now power advanced chat tools used by both customers and internal service teams. “In one team, 10 percent of service interactions are fully handled by agentic AI,” he said.
The result? Faster cycles of innovation and more effective knowledge sharing across a complex, global organization.
Looking Ahead: A New Age of Intelligence
For Partovi, the excitement around AI and generative technology hasn’t dimmed; it’s accelerating. He likens today’s moment to past tectonic shifts: the agricultural revolution, the industrial revolution, the rise of computing.
“We’re now entering the age of intelligence,” he said. “For the first time, you can embed reasoning and action into digital tools. This changes everything.”
From closing care gaps in underserved regions to transforming daily workflows in hospitals, Partovi sees AI as the engine that will finally deliver on healthcare’s promise of access, equity and personalization. “We’ve dreamed about using technology to close the healthcare gap,” he said. “Now we finally have the tools to do it.”
In today’s digital landscape, where user engagement directly correlates with product longevity, the stakes for developing user-centric products have never been higher. Success demands not just initial user understanding, but a continuous cycle of testing, learning, and iterating to refine products based on real-world usage and feedback. When technology product teams rush to build solutions before establishing this foundational cycle, they overlook critical user needs, mistakenly believing they’re accelerating delivery. Organizations that bypass this iterative approach don’t just risk poor adoption rates—they jeopardize their entire product lifecycle and, ultimately, their market position. Yet despite these evident risks, many companies still find themselves in reactive modes, struggling to retain customers and maintain market relevance.
This challenge stems from a complex interplay of organizational dynamics that extends far beyond simple oversight. When technology product teams craft their strategic vision, they often rush to build solutions before fully understanding what users truly need, mistakenly believing this accelerates delivery. This approach, while seemingly efficient, leads to misaligned products that fail to resonate with their intended audience. The reality is that user requirements must be the foundation of product strategy—not an afterthought—and should be shaped by those closest to the user experience.
Our work with organizations across industries has revealed a consistent pattern: companies that do not invest adequate time in upfront user understanding and ongoing iteration inevitably pay the price in form of multiple product iterations and customer dissatisfaction. When combined with aggressive timelines and insufficient user data, this creates a perfect storm that not only undermines product success but also strains organizational resources and team morale.
Through careful analysis of successful product-centric transformations, we have identified five fundamental steps that enable organizations to pursue customer centric product design. These steps aren’t meant to be executed once and forgotten, but rather form a continuous cycle of learning and improvement:
By embracing this framework, organizations can transform their approach to product development. Instead of navigating uncertain returns and user indifference, teams can create products that consistently delight users and drive sustainable business growth. This systematic approach not only enhances product success rates but also establishes a foundation for continuous innovation and market leadership.
To illustrate how these steps transform product development in practice, let’s take a look at a product team tasked with reimagining the customer checkout experience for an eCommerce platform. Composed of Design, Engineering, and Product roles, the team recognizes that successful product development requires seamless collaboration across these critical functions—each bringing unique perspectives that collectively unlock user-centric innovation. Guided by executive leadership’s strategic mandate to reduce customer drop-off rates and improve conversion metrics, the team oversees both web and mobile interfaces and faces a critical challenge: high customer abandonment after cart additions, directly impacting revenue and customer satisfaction. With clear directives from senior management to develop a comprehensive strategy that balances user needs with business objectives, the team must rapidly identify pain points and craft innovative solutions. Under the guidance of an experienced Product Manager, they embark on a systematic journey to uncover user challenges and transform the checkout experience from a point of friction to a competitive advantage.
Image 1: Cross-Functional Team Integration: Ensuring seamless collaboration between Product, Design, UX, and Engineering to aid the product discovery process
To develop customer-centric products, it’s essential to first understand who the product team is designing the experience for. Defining the customer persona is not just a step in design thinking—it is the foundation of a successful product strategy. By clearly outlining user preferences, challenges, and motivations, teams can ensure their solutions are relevant and impactful. Keep in mind that customer persona can represent either a customer or an employee, depending on the product’s focus.
Once a comprehensive persona is created, teams should map out the user’s current experience. Journey maps visually represent the customer’s interactions with the product, enabling teams to identify friction points and tailor enhancements.
For example, the checkout team’s persona might be a 37-year-old working mother of two, often shopping in a rush. Her journey could include:
By understanding these stages, product teams can address user preferences holistically, ensuring that improvements align with both immediate and long-term goals.
After mapping the stages and understanding how customers engage with the app, the next step is to evaluate the pain points they encounter. The ‘jobs-to-be-done’ framework can help product teams understand that users choose products to accomplish specific tasks. By outlining these jobs, product teams can define desired outcomes, segment them and devise strategies to address them. This approach not only fosters empathy for user challenges but also provides actionable insights to define the desired future state.
For the checkout team, this might involve analyzing app usage, metrics, and customer feedback to pinpoint issues like:
Mapping these pain points to the identified journey stages, enables the product team to create a comprehensive overview of specific pain points across the customer journey.
With a clear understanding of user personas and pain points, teams can envision the ideal future-state experience. This critical step requires a nuanced approach that balances user preferences with technical feasibility and business constraints. While user feedback is invaluable, product teams must recognize that not every user suggestion represents a viable or optimal solution—some ideas may introduce unintended complexity or misalign with broader product strategy.
For the checkout team, crafting an ideal experience means carefully prioritizing enhancements that deliver maximum user value while remaining technically and strategically sound:
During a recent engagement with a leading technology company’s mobile application team, this strategic approach enabled the client to boost user engagement and streamline upselling opportunities. By defining an ideal experience that balanced user desires with technical constraints, the team could allocate resources effectively and build toward a cohesive vision.
Once the future state is defined, product teams must identify the capabilities required to bridge the gap. Developing these capabilities proactively—rather than merely reacting to user feedback—empowers teams to anticipate needs and deliver innovative solutions that surprise and delight users.
Leadership support is essential to ensure teams have the resources and authority to pursue these enhancements efficiently. For the checkout team, this might mean prioritizing:
By focusing on proactive development, teams can release iterative changes more rapidly and achieve a continuous cycle of improvement.
Finally, measuring success is as critical as defining the vision. Product teams must identify key performance indicators (KPIs) that align with the desired user experience and overarching business goals. Well-defined KPIs enable teams to validate assumptions, track progress, and refine strategies in real time, making them an integral part of a mature dual-track discovery and delivery process.
For the checkout team, KPIs such as site loading times and drop-off rates provide tangible benchmarks for success. These metrics not only indicate the immediate health of the product but also serve as early signals of deeper issues or opportunities.
Establishing a metrics-driven approach not only elevates the team’s problem-solving capabilities but also creates a culture of accountability and continuous learning. When both product teams and leadership actively engage with KPIs, they foster an environment where decisions are based on evidence rather than assumptions, paving the way for long-term success and innovation.
Through the application of these five steps, the eCommerce checkout team transformed their approach to product development. By deeply empathizing with their users, mapping the customer journey, and methodically addressing pain points, they gained invaluable insights that traditional feature-driven development would have missed. Their systematic approach to defining the future state and identifying necessary capabilities ensured that every enhancement addressed user needs, ultimately resulting in meaningfully lower drop-off rates and higher customer satisfaction.
This framework, though straightforward, opens doors to broader strategic considerations. Teams must handle capability prioritization, cross-functional responsibilities, and resource allocation—challenges that extend beyond any single product team’s domain. Yet these challenges are worth tackling, as they lead to more cohesive, user-centric solutions.
The path to user-centric product development requires more than just following steps—it demands a fundamental shift in how organizations approach product strategy. Success is dependent on leadership’s commitment to empowering teams with both the framework and the organizational support to execute it effectively. By establishing a dual-track discovery and delivery process, teams can maintain their user focus while delivering tangible results. This balance between user needs and business objectives, supported by clear vision and strong change management, creates the foundation for products that truly resonate with users and drive sustainable business growth.
Image 2: Illustrative E2E Product Discovery & Delivery Product for Product Teams
Highlights from our recent Metis Strategy Summit are below. Check out our Youtube channel and Technovation podcast in the coming weeks for recordings of the conversations.
Organizations across industries are moving beyond initial AI experimentation, focusing on driving implementation, proving and measuring ROI, and developing the next generation of talent as they apply AI to a broader number of business challenges.
As multiple executives emphasized, strong data foundations are essential to any successful AI implementation. Marina Bellini, President of Global Business Services at Mars, noted that the hype around AI has led to more focus on ensuring those foundations are in place. “This is the dream of the CIO: that people will actually start working on data quality.”
This year has also seen increased focus on AI’s ability to deliver value. Augment CEO Scott Dietzen said 2024 “is the year where tech teams are looking for proof and return on investment,” something not always clear or easy to measure for software such as Copilot productivity tools.
Organizations are finding new and innovative ways to apply data and AI to business challenges. Royal Caribbean Group CIO Martha Poulter described how the company transformed traditional food service operations into data-driven processes. Initially, “you would order what you thought, cook what you thought, and serve what you thought. It was gut based,” she explained. By measuring proteins before and after cooking and analyzing everything from ordering to de-thawing to waste, Royal Caribbean was able to generate tens of millions in savings while improving sustainability. “You’d never think food can be an AI problem, but it is,” Poulter said.
Similarly, Avis Budget Group is using an AI-based modeling and prediction system to address asset utilization challenges and ensure cars are on the road for the greatest amount of time. Chief Digital & Innovation Officer Ravi Simhambhatla explained how the company is aiming to break through the 70% utilization ceiling for its vehicle fleet. “If you have physical assets that aren’t being utilized, it’s costing the company money,” he said. “We hit this glass ceiling and asked ourselves why can’t we go to 80% or 90%? It turns out it’s data.”
Technology leaders discussed various approaches to managing and organizing AI initiatives across their organizations. A common thread across nearly all of them was the importance of bringing together technology and business leaders to identify valuable use cases and deliver on them faster. NRG’s Chief Data and Technology Officer, Dak Liyanearachchi, talked about establishing a transformation office that bridges data, business, and technology teams. At Berkadia, an AI Council that includes both business partners and technology leaders drives deeper engagement and keeps discussions focused on value, Chief Information and Innovation Officer Damu Bashyam said.
As mentioned throughout the event, these new organizational structures place particular emphasis on modern technology stacks and data practices. Nicholas Parrotta, Chief Digital and Information Officer at HARMAN International, outlined the company’s evolution from infrastructure-as-a-service to data-as-a-service, and using that data to create more personalized experiences on wheels as the world moves toward autonomous vehicles. “We start with how we do the big stuff with architecture, then product, and now data and being able to drive those as revenue and capabilities,” he said.
Capital One CIO Rob Alexander detailed the company’s platform strategy, explaining how the organization built dedicated infrastructure for machine learning, feature engineering, and now generative AI applications. When it comes to AI, he noted that while it’s “easy to get 70% accuracy out of the box, all the work is getting from 70-75% accuracy, which involves training and fine tuning.” Being in a position to leverage AI today has been a 12-year journey for Capital One, Alexander said, one that has included transforming “everything about who we are” to become a successful technology company and a winner in the banking industry.
Leaders emphasized the need for pragmatic approaches to AI implementation. Mastercard CTO Ed McLaughlin noted three questions a review panel considers when evaluating the feasibility of a new AI initiative: “Does it work, is it worth doing, and does it align to our ethics?” If ChatGPT-style search responses are 10 times more expensive than traditional methods, for example, the question then is whether they can deliver 12 times more value or be that much more useful. McLaughlin underscored the need to assess both the right way to solve a particular problem and whether there are returns on the work being done.
Dietzen added that NPS and engineer satisfaction can also be indicative of value. “If you make engineers delighted, you’ll tend to do well in your organization,” he said.
Chris Davis, Partner and West Coast Office Lead at Metis Strategy, advises technology leaders to ensure that there is product management in every layer of the AI stack, including the application of AI to business processes, the marketplace of horizontal and reusable capabilities across use cases, and underlying foundational models and model development. Business value should be measured relative to components of the stack, especially with generative AI, Davis said.
Effective product management requires teams across the organization to sharpen their product mindset. Cigna’s Chief Digital & Analytics Officer Katya Andresen outlined three elements of that product mindset: identifying real problems for real users, validating through testing and learning, and unlocking value. She cautioned against common pitfalls like “death by a thousand pilots,” in which proofs of concept pile up and eventually become unmanageable. Organizational silos can present a challenge. “We find a lot of opportunities to streamline operations, but there has to be a really deep partnership across tech and ops,” she said. Otherwise, “tech gets upset that ops don’t use their products and ops says well what you gave us didn’t solve our problem.”
Organizations are rethinking their talent development strategies as the landscape evolves. That involves both upskilling internal talent and expanding talent pools across geographies. Land O’Lakes CTO Teddy Bekele described moving from a roughly 50-50 mix of in-house and external talent to a model in which contractors and third parties make up a more significant portion of the talent pool, taking on much of the development work while in-house employees lead the teams. The approach allows for increased flexibility in team sizes depending on shifting enterprise needs. The change was driven by three key factors: accessing expertise, maintaining flexibility to scale teams up or down, and increasing nimbleness.
Upskilling also remains a key focus. At FINRA, Chief Technology Engineering Officer Tigran Khrimian’s team is teaching developers generative AI skills and has seen demonstrable success with using natural language prompting to create “good code” for the company. “Developers with code assistant tools will replace developers who don’t use them,” he said.
Corning’s Chief Digital and Information Officer Soumya Seetharam detailed the company’s three-pronged approach to talent development: creating strategic digital and IT hubs around the world to ensure global talent access; launching a digital literacy program with dedicated “revitalization days” for learning rather than meetings; and expanding the talent pipeline through technology internship and rotational development programs globally. “In the future every person for every function will have some technology in their background,” she predicted.
Technology leadership roles are undergoing significant transformation, reflecting the strategic importance of technology in business operations. According to Katie Graham Shannon, global head of the Digital and Technology Officers Practice at Heidrick & Struggles, the traditional CIO title is becoming less common. Of 23 recent technology leader placements at Fortune 200 companies,18 did not have the CIO title, and 52% were newly created positions with expanded roles. She noted that there is also a shift in reporting structures, with more CIOs reporting to the CEO, and a greater focus on technology leaders’ ability to create and protect value and attract talent, among other responsibilities.
“If we could use the title ‘orchestrator’ it would make more sense,” Shannon added, explaining that today’s technology leaders create value and orchestrate initiatives across the entire C-suite. This expanded scope includes both customer-facing initiatives and internal operational efficiencies with “equal pressure and emphasis” in both areas.
The role is also becoming more business-oriented, particularly in relation to managing technologies like AI. “A properly formatted conversation about AI is not a tech conversation, it’s a business conversation,” observed Henry Man, Co-Founder and Managing Partner at Candela Search. This presents an opportunity for technology leaders to “have a seat at the table” when business colleagues might lean out of technical discussions.
That expanded purview extends to technology leaders on boards or seeking director positions. “There’s no market for a one-issue board member,” said Art Hopkins, who leads the Technology Officers Practice at Russell Reynolds. “You need to show business acumen and a P&L. Go to the CEO and say I’d like to be the executive sponsor of this new incubator. This is a solid step in that direction.”
We are thrilled to announce that our Metis Strategy Summit will take place live in New York City. On Oct. 29 from 9 a.m. to 5 p.m., we’ll hear from technology leaders, investors and entrepreneurs about the trends shaping the business and technology landscape today, from the rapid rise of generative artificial intelligence to the macroeconomic and geopolitical shifts impacting global organizations. Other topics include:
Please note, this is an invite-only event for C-level technology leaders. If you are interested in attending, click here to request an invitation. Stay tuned for a venue announcement and agenda updates coming soon. We look forward to seeing you in New York!
Download pdf, 2.11 MB
Click here for highlights from our most recent Digital Symposium, and stay tuned to our YouTube channel for videos of our panel discussions.)
8:30 a.m. – 9:00 a.m.Registrant Check-in
Arrive early to check in and collect your event materials. This time allows you to settle in, familiarize yourself with the venue, and start connecting with other attendees before the day’s sessions kick off.
Additional arrival information will be distributed to ensure a smooth start to your day.
9:00 a.m. – 9:15 a.m.Welcome and Opening Remarks
Peter High, President of Metis Strategy, kicks off the event with a brief introduction of the day’s sessions and the Metis Strategy team.
9:15 a.m. – 9:45 a.m.AI-Driven Customer Experience
This discussion will explore how organizations are using AI to deliver more personalized and dynamic experiences for customers and employees, and how the digital customer experience is evolving in the era of generative AI agents and more powerful models
9:45 a.m. – 10:15 a.m.Project-to-Product’s Next Frontier
The ongoing shift to product-oriented operating models has begun to erode the traditional silos between business and IT and presented technology leaders with new opportunities and challenges. This panel will examine the future of the product model as companies become increasingly experience-centric and AI becomes a bigger part of the equation.
10:15 a.m. – 10:30 a.m.Entrepreneur Spotlight: Augment CEO Scott DietzenThe rise of generative AI sparked a wave of coding assistants promising new paradigms for software development and greater productivity. In this panel, Augment CEO Scott Dietzen will share insights on the current state of the industry and where coding assistants are headed next.
10:30 a.m. – 10:50 a.m.Coffee and Networking Break
Take a moment to grab a coffee and meet fellow attendees. This break offers a great chance to start conversations, share perspectives, and establish connections that will enrich the discussions throughout the day. Use this time to engage with industry leaders and peers before diving into the sessions.
10:50 a.m. – 11:20 a.m.To Innovate at Scale, You Have to Modernize. How Companies Balance Both.
To take advantage of the latest technologies, organizations need a modern tech stack. At the same time, they need to ensure necessary legacy systems don’t become a drag on progress. In this session, panelists will share how they are driving ambitious modernization roadmaps and creating the mindset for change.
11:20 a.m. – 11:50 a.m.Advancing Data Strategy and Measuring AI’s ValueAs AI experiments have flourished, technology leaders are now focused on another acronym: ROI. Panelists will share how they are measuring AI’s business value, identifying initiatives that will drive the greatest impact inside their organizations, and ensuring a strong data strategy to guide it all.
11:50 a.m. – 12:05 p.m.Fireside Chat: The Path from CIO to CEO Mike Clifton joined Alorica as CIO in 2021. This spring, he was named Co-CEO. The former technology and operations leader at Cognizant, Federal Home Loan Bank of Boston, and the Hanover Insurance Group, among others, will share lessons learned throughout his journey and offer tips for CIOs seeking to expand their purviews. He is joined by fellow Co-CEO Max Schwendner.
12:05 p.m. – 1:05 p.m. Lunch and Networking Break
Recharge and refuel while continuing the conversation with colleagues and new connections. Whether deepening discussions from the morning sessions or exploring fresh ideas, this lunch break offers the perfect setting for meaningful exchanges in a more relaxed environment.
1:05 p.m. – 1:35 p.m.Next-Gen Talent Operating ModelsIn today’s talent landscape, a mindset of continuous learning is key to success. This session will explore how companies are upskilling their teams for the future while navigating a world of work in which tech and business teams are more intertwined than ever.
1:35 p.m. – 2:05 p.m. Responsible AI: Value Proposition and Opportunities Operationalizing AI is widely believed to be a compelling and potentially game-changing value proposition but one that comes with a myriad of unique and dynamic risks. Organizations are therefore aiming to practice “responsible AI”, the development, deployment, and use of AI capabilities in a transparent, accountable, legal, and ethical manner. Panelists share their insights and approaches for developing and deploying AI responsibly for the benefit of their respective organizations and their many stakeholders.
2:05 p.m. – 2:20 p.m.Unlocking ROI: Cloud Strategies for the Next AI Wave
This session will explore the symbiotic relationship between cloud and AI, the modernization decisions CIOs can make now to prepare their companies for the next AI wave, and the workload considerations needed to ensure newfound AI efforts deliver ROI.
2:20 p.m. – 2:50 p.m.The Expanding Innovation Ecosystem
Technology leaders today understand that new ways of thinking don’t come only from inside an organization’s four walls. These leaders will share how they are leveraging external partners, peer networks, and new innovation frameworks access to new technologies becomes ever more democratized,
2:50 p.m. – 3:05 p.m.Fireside Chat: Tanium CEO Dan StreetmanAs hackers get more sophisticated and new tools proliferate, today’s cybersecurity landscape is more complex than ever. In this discussion, Tanium CEO Dan Streetman shares how technology leaders can manage through that complexity and protect their organizations from the next wave of threats.
3:05 p.m. – 3:35 p.m.The Changing Role of the Technology Leader: Executive Recruiter Perspectives
The role of today’s digital and technology leaders seems to be changing as quickly as the technology they oversee. In this panel, executive recruiters share perspectives on how the title and purview of the modern technology executive is evolving as advances in AI and other innovations reshape organizations around the world.
3:35 p.m. – 3:50 p.m. Fireside Chat: Remaining Nimble and Resilient in a Constantly Changing World With the US Presidential election just days away and the global economic outlook in flux, companies across the globe are preparing for a variety of scenarios that could impact their strategies going forward. In this fireside chat, the Co-Head of the Goldman Sachs Institute will discuss how technology leaders can put their organizations in a position of readiness and resilience as they prepare for the opportunities and challenges ahead.
3:50 p.m. – 4:00 p.m.Closing Remarks
Peter High, President of Metis Strategy, will reflect on the day’s key takeaways and the insights shared both onstage and off. As the event draws to a close, Peter will set the stage for future discussions on innovation, technology leadership, and transformation.
4:00 p.m. – 5:00 p.m.Reception
Enjoy light refreshments and continue the conversation in a more casual setting. The reception provides a final chance to network, solidify new relationships, and unwind with peers after a full day of learning.
(Click here for highlights from our most recent Digital Symposium, and check out our YouTube channel for videos of the panel discussions.)
This article was written by Leila Shaban, Research Associate at Metis Strategy
Thank you to everyone who attended and participated in the 17th Metis Strategy Digital Symposium. Highlights from the event are below. Check out Metis Strategy’s Youtube channel and Technovation podcast in the coming weeks for recordings of each conversation.
Companies continue to make progress in their AI journeys, deploying the technology to drive efficiency, productivity and innovation. Technology leaders are focused now on driving adoption, generating buy-in for new initiatives, and rolling out new training programs to ensure teams across the enterprise are able to take advantage of what AI has to offer. Below are a few highlights from the event:
Building a foundation for AI at scale
Nearly all CIOs on stage said scalable infrastructure and high-quality, accessible data are key to driving value from AI initiatives. Over the past few years, many organizations have focused on building data platforms, shifting to cloud and rethinking ways of working in order to deliver AI at scale. “Having a really good data infrastructure is foundational to taking advantage of any of these generative AI capabilities,” Priceline CTO Marty Brodbeck said. Many speakers noted their current efforts to get reliable data into the hands of more teams across their organizations.
Nearly half of MSDS attendees said that the rapid evolution of AI, among other macro issues, will have the biggest impact on their organizations in the year ahead
Exploring new use cases
Many organizations continue to train generative AI on internal knowledge bases to streamline processes and enable more self service. CIOs also see potential around developer productivity.
Bristol Myers Squibb receives thousands of calls from physicians and nurse practitioners each day requesting information about specific, often technical, topics, Chief Digital and Technology Officer Greg Meyers said. MDs on the other side of the call often find those answers in internal documents. Now, an AI chatbot trained on the company’s knowledge base can search through the documents to retrieve answers to these questions much faster. With enough fine tuning, Meyers noted the chatbot could constrain search results to trusted documents and help agents provide near-immediate answers to customer queries.
At UPS, Chief Digital and Technology Officer Bala Subramanian recently launched an internal AI tool for email which can process the tens of thousands of customer emails UPS receives on a daily basis, connect relevant information across internal policies and procedures, and generate responses for contact center employees. This ultimately improves worker productivity and reduces response time. UPS also launched an AI chatbot to help employees answer HR questions. Subramanian noted that the company is proceeding slowly due to the sensitive information and personal data in HR systems, and emphasized the critical role of risk management and governance.
At AstraZeneca, AI is significantly reducing the amount of time it takes to conduct research. Cindy Hoots, Chief Digital and Information Officer, described a generative AI-enabled research assistant that quickly searches both internal and external data to answer complex scientific questions. The assistant has helped reduce the time it takes to conduct a literature review from months to minutes, she said. Hoots is now focused on scaling AI adoption. About 15,000 employees use the research assistant, she said, while roughly 5,000 use Copilot solutions and almost 80,000 have access to AstraZeneca’s internal ChatGPT.
At KB Home, employees evaluate a number land deals across 35 markets every week. Aggregating property data from different sources to determine whether to make an acquisition used to take 30-90 days, CIO Greg Moore said. With AI, KB Home can now complete the process in less than two weeks. The faster turnaround now enables the company to make more evaluations and manage more potential deals in the pipeline.
Developer productivity is another area of rapid experimentation. Many of the tools offered by major vendors are in their early days and have room to grow, said Brodbeck of Priceline. The team is exploring solutions that can learn from Priceline’s codebase and provide a richer and more contextual experience. Whether for code generation or another use case, Brodbeck said companies will likely need to deploy retrieval-augmented generation (RAG) to deliver more productivity.
At Augment, CEO Scott Dietzen is thinking about how to retrieve knowledge from internal codebases in a way that protects intellectual property and reduces the risk of leaking sensitive information. The team started with basic engineering tasks that can make developers more productive rather than trying to replace them altogether. Demand for these kinds of tools will last for at least a decade as organizations produce more software, Dietzen said.
The top use cases for digital assistants/copilots that are driving the most value for MSDS attendees are code generation, self-service chatbots, and enterprise search/knowledge management
Bringing the organization along on the AI journey
To drive a common understanding and widespread adoption of AI, CIOs have increased their focus on storytelling and talent development.
At Wilson Sonsini, Chief Information Officer Michael Lucas is focused on cascading AI communications across the firm. His team started with a general awareness campaign. That included employee town halls to communicate the broader strategy as well as AI-centric briefings to partners. Given the sea of media coverage about AI, Lucas encouraged leaders to develop their own elevator pitch to help their organizations clearly understand the company’s AI strategy. Driving a common understanding across the firm is key to driving adoption. “We feel like we need to learn, understand, enrich, and then apply and operationalize,” Lucas said.
At Liberty Mutual, Global Chief Information Officer Monica Caldas is delivering customized employee training and connecting it to the company’s capacity demands across 27 countries. It’s part of a workforce strategy plan called “skills to fuel our future.” First, the company surveyed more than 5,000 employees to determine their skill level around topics like data, data engineering and software engineering. Next, the company mapped over 150 skills, connected them to 18 domains, and assessed how and where to invest in training.
Now, Caldas and her team are helping employees apply that training to a variety of career paths. Instead of a traditional career development ladder, Liberty Mutual is evaluating how to map skills to different jobs and create a “jungle gym” or “lattice of opportunities.” The focus on specific skills, Caldas said, “will help you position your capabilities as a tech organization not just for today, but also plan out where it’s going.”
Education at the executive level is also critical. To bring executives along on the journey, Caldas introduced a program called Executech that helps improve organizational data literacy and elevates the digital IQ of decision makers. Enhancing teams’ tech acumen gives leaders the confidence to start conversations early about important technology topics like API integration.
AI adoption may not be uniform, and there is still lots to learn about how it will impact specific roles. At Eli Lilly, employees who have incorporated AI tools into their workflow are reluctant to give them up, said Diogo Rau, Chief Information and Digital Officer. However, widespread adoption is a continuous and sometimes challenging process, “a lot harder than anyone would guess,” Rau said.
Rau often gets more questions about the risks of AI than how it can be used to improve products and services. Another challenge is that teams excited about creating AI bots aren’t always excited about maintaining or training them. “There are lots of good firefighters, but not every firefighter wants to be a fire inspector,” he said.
62% of technology executives who attended the Metis Strategy Digital Symposium anticipate that the most significant impact that AI will have on talent is increased productivity
Leveraging ecosystem partners
Achieving the transformative potential of generative AI will require collaborating with networks of vendors, startups, peers, and academics. In addition to providing technology solutions, these ecosystem partners can help upskill employees, explore emerging challenges, and prototype new use cases.
Amir Kazmi, Chief Information and Digital Officer at WestRock, draws learnings from both established technology partners and startups. He also brings in academics and peers from other companies to share wins and lessons learned about generative AI.
Regal Rexnord’s Tim Dickson, Chief Digital and Information Officer, uses hackathons and internal events with vendor partners to increase the company’s digital IQ. The company also offers self-paced training from about 10 partners that includes pathways to certification. In the past seven months, more than 100 employees have received training on GenAI fundamentals from Databricks and robotic process automation from UiPath, as well as certifications from Microsoft Copilot. Even if employees don’t use these tools every day, increasing the number of people with technical skills means more individuals “can at least help, or even lead, these initiatives across the organization,” Dickson said.
CommScope CIO Praveen Jonnala, like many other technology executives, is thinking about how to drive a cultural shift around AI. He spends about 80% of his time on organizational change management and culture. He is also leaning into existing partnerships to take advantage of new AI solutions and educate teams. For example, he took business teams to Microsoft for a full day to learn more about the technology and its ability to unlock new business opportunities.
Advancements in artificial intelligence have opened the door for innovative ways companies can deliver unique and personalized customer experiences. Join us virtually on May 21 for our next Metis Strategy Digital Symposium where global business and technology executives describe how AI has improved their organizations, how they are continuing to foster a customer-centric mentality, and what the future of technology and digital looks like in the Age of AI.
C-level technology leaders, register here reserve your spot and stay tuned for agenda updates. We look forward to seeing you!
(Click here for highlights from our most recent Digital Symposium, and stay tuned to our YouTube channel for videos of our panel discussions.)
12:00 – 12:15 p.m.
Welcome and Introductions
Welcome and introduction to the Metis Strategy team
Peter High, President, Metis Strategy
12:15 – 12:40 p.m.
Customer Experience in the Age of AI
Marty Brodbeck, Chief Technology Officer, Priceline
Bala Subramanian, Chief Digital & Technology Officer, UPS
Moderated by Steven Norton; Co-Head Executive Networks, Research, and Media; Metis Strategy
12:40 – 1:05 p.m.
Driving Digital Innovation Ahead of Disruption
Greg Moore, Chief Information Officer, KB Home
Michael Lucas, Chief Information Officer, Wilson Sonsini
Moderated by Chris Davis, Partner & West Coast Office Lead, Metis Strategy
1:05 – 1:30 p.m.
Shaping the Story: Future-Oriented Talent and Innovation
Monica Caldas, Global Chief Information Officer, Liberty Mutual
Amir Kazmi, Chief Information & Digital Officer, WestRock
Moderated by Alex Kraus, Partner & East Coast Office Lead, Metis Strategy
1:30 – 1:45 p.m.
Entrepreneur Spotlight: CEO of Augment
Scott Dietzen, CEO, Augment
Moderated by Peter High, President, Metis Strategy
1:45 – 2:15 p.m.
Emerging AI Opportunities in Pharmaceuticals and Healthcare
Diogo Rau, Chief Information & Digital Officer, Eli Lilly
Cindy Hoots, Chief Digital Officer & Chief Information Officer, AstraZeneca
Greg Meyers, Chief Digital & Technology Officer, Bristol Myers Squibb
2:15 – 2:40 p.m.
Blueprint for AI Organizational Readiness
Praveen Jonnala, Chief Information Officer, CommScope
Tim Dickson, Chief Digital & Information Officer, Regal Rexnord
Moderated by Michael Bertha, Partner & Central Office Lead, Metis Strategy
2:40 – 2:55 p.m.
Closing Remarks and Adjourn
Click here for highlights from our February Metis Strategy Digital Symposium, or watch the panels on our YouTube channel. We look forward to seeing you!
Thank you to everyone who participated in the 15th Metis Strategy Digital Symposium. Check out some event highlights below, and stay tuned to the Metis Strategy YouTube channel and Technovation podcast in the coming weeks for full sessions.
For businesses across the globe, 2023 was the year of generative AI. Since ChatGPT’s launch and meteoric rise last November, digital leaders have been experimenting with a range of new GenAI products and services as they searched for the most effective, and least risky, way to bring the technology to their organizations. As GenAI (and the hype around it) took off, it prompted important and complex conversations about the future of work and how to accelerate innovation while managing new and significant risks.
A little over a year in, leaders continue to experiment with new tools as a means to drive new value and improve the experience for customers and employees. They are also turning their focus back to the fundamentals, building strong data governance and data hygiene practices to ensure their organizations have the strategic and operational foundation needed to take advantage of their data.
GenAI is still the shiniest thing out there, but as technology leaders look to 2024, they are focused on integrating it, and AI more generally, into their organization’s operating model and championing use cases that can produce tangible value at scale.
If year one of generative AI was about deciphering its risks and enabling organizations to experiment safely, year two will be about finding ways to drive value at scale. With new use cases emerging regularly, technology leaders are figuring out how to prioritize the initiatives that show the most promise to the business.
At BNSF Railway, CIO Muru Murugappan and his team use a value feasibility matrix to assess technical feasibility, timing, and complexity of new AI initiatives versus the expected payback. Some companies are also using business interest and executive sponsorship as criteria for deciding which initiatives to pursue. One overarching lesson: the more ambitious the project, the more challenges it is likely to face.
In addition to delivering on generative AI’s opportunities, CIOs now are contending with a new set of costs as well. Speakers also highlighted the fact that simply “turning on” a new AI tool does not guarantee value.
For many, the path to unlocking AI’s value means getting back to basics. “This is reinforcing the need for analytics fundamentals,” said Filippo Catalano, Reckitt’s Chief Information & Digitisation Officer. “If you don’t have good data practices, at best you’re going to use whatever others are using, but you will not be able to generate competitive advantage. Great data practices … become even more important.”
While new AI tools have helped organizations explore the art of the possible, they also have created a number of new risks, from more advanced cyberattacks to the negative impact of training algorithms on biased data. Just over one quarter of attendees cited data privacy as the largest AI-related risk to their organizations. The delicate balance for CIOs: managing the new risk landscape while empowering teams across the organization to experiment and innovate.
Martin Stanley, who leads the Cybersecurity and Infrastructure Security Agency R&D portfolio, is currently assigned to the Trustworthy and Responsible AI program at NIST. Among his team’s goals is promoting adoption of the AI Risk Management Assessment Framework, which provides a construct for deploying AI responsibly and managing risk among a diverse set of stakeholders. The framework means to address a few key concepts: building a language around AI risk beyond simply monitoring potential vulnerabilities, creating a shared understanding of how to manage that risk across the enterprise, and driving a trust-driven, “risk- aware culture” that influences how people interact with the technology.
CIOs are working to build trust into every layer of the process. As Vishal Gupta of Lexmark noted, technology is only as good as people’s ability to adopt it and trust what it’s saying. “Otherwise, you really can’t do much with it.” At Lexmark, Gupta is taking a layered approach, creating trust in the underlying data via stronger governance and management practices; driving trust in AI and machine learning models by setting up an AI ethics board and rigorously vetting use cases; and continuously testing to validate AI’s ability to truly drive business outcomes.
New AI tools such as developer copilots have the potential to drive significant productivity gains and reshape how many of us do our jobs. As humans and technology continue to interact in new ways, CIOs are focused on optimizing the digital employee and customer experience while helping teams navigate a changing world of work. Indeed, 50% of MSDS attendees plan to apply AI and generative AI to impact employee experience and productivity, with 30% planning to use it to improve the customer experience.
At TransUnion, CIO Munir Hafez and his team are taking a human-centered approach to the digital experience with a focus on ensuring tech equity and establishing policies that allow teams to safely experiment with new tools, among other initiatives. When investing in employee experience, “our goal was to create a consumer-grade experience that enables employees to be engaged and productive in an environment that is integrated, modern, frictionless, and connected anywhere,” Hafez said.
AI’s ability to deliver frictionless employee experiences and deliver real productivity gains far beyond IT is likely to be a big focus for 2024. Many panelists noted how access to accurate, AI-enabled real-time data can help field managers make decisions more quickly, and how technologies like digital twins can streamline design processes and speed time to market.
Navigating an uncertain economic environment and rapid technological advances are top of mind for CIOs in the year ahead. The convergence of these two factors continues to underscore the importance of bringing a strategic, value-based lens to AI development and adoption.
The hype around generative AI may come back down to earth in 2024 as companies begin to understand its complexities in the enterprise. “I think there is going to be…a little bit of a trough that we’ll hit with GenAI,” said Graphic Packaging International CIO Vish Narendra. “The commercialization of that is going to take a little longer in the enterprise than people think it’s going to.”
As technology becomes embedded across a broader range of products and services, the spotlight will be on CIOs to show the art of the possible, create future-ready workforces, and manage risk. Given their broad purview that spans horizontally across organizations, CIOs are well positioned to influence and shape enterprise strategy in the year ahead, setting their companies up for continued resilience and growth.
