As strategy and transformation leaders know, true business transformation isn’t just about technology—it’s about reshaping how companies operate to deliver sustained value. That means aligning digital investments with customer needs and empowering employees to drive meaningful change. Without engaged teams, even the most ambitious efforts risk falling short. And without clear customer impact, transformation becomes an exercise in efficiency rather than progress.

One of the biggest challenges leaders face is ensuring transformation efforts don’t become isolated projects. Organization-wide change requires a mindset shift, embedding customer-centricity at every level and rethinking how teams collaborate, make decisions, and leverage technology to deliver value. And that starts with people.

Lasting transformation depends on employees embracing change. Hiring for adaptability is critical, but it doesn’t stop there—in today’s dynamic environment, the ability to learn and evolve is often more valuable than technical skills. Some leaders even prioritize candidates who may not have deep expertise in a specific role but demonstrate curiosity, resilience, and the agility to navigate new challenges.

Hiring adaptable talent is one piece—sustaining it is another. The rapid pace of AI-driven change can create uncertainty and resistance. Leaders must reskill their workforce to overcome the “fear factor” and help employees reframe how they approach work in an AI-enabled world. Confidence in new ways of working matters more than the technology itself. This requires genuine empathy—experiencing frontline challenges, practicing active listening, and co-creating solutions that address real needs.

Leaders must also embrace a learner mindset. Reverse mentorship, where leaders learn from the next generation, is a powerful way to bridge experience with fresh perspectives. When organizations encourage bidirectional learning, they create a culture where employees at every level feel valued, engaged, and empowered to drive transformation.

However, proving the value of these efforts remains a challenge. Many organizations fall into the trap of measuring success solely through operational efficiency. While important, these metrics don’t always reflect whether transformation efforts are driving real customer value. Forward-thinking leaders focus on how well their companies meet evolving customer needs. Empowered employees—those who are engaged, adaptable, and attuned to customer challenges—are the ones who drive meaningful business outcomes.

As one executive put it: “We have a responsibility to ensure that every single dollar we invest delivers tangible value for our customers and stakeholders.“

The key takeaway? Transformation is an ongoing process powered by people, for people. To start or accelerate this journey, consider:

• Are your employees empowered to solve real customer challenges?
• Do your transformation efforts align with evolving customer needs?
• How well does your organization integrate and act on customer feedback?
• Can your workforce quickly adapt to change without losing focus on customer value?

By embedding customer-centricity, investing in employee empowerment, and measuring success beyond efficiency, companies can turn transformation from an abstract goal into a lived reality—one that delivers real impact for both employees and customers alike.

CDOs are navigating a complex AI adoption landscape, balancing speed, security, and business impact while managing the pressures of delivering measurable value. The question today isn’t whether AI will be transformative—that’s long been clear. The real challenge is: How can CDOs move from AI experimentation to execution and scale?

Too often, companies fall into one of three AI traps:

• Paralysis—unsure where to begin amid AI hype
• Endless experimentation—stuck in pilots with no clear path to scale
• Overengineering—waiting for AI to be perfect instead of “good enough“ to drive impact

For many leaders, hesitation stems from broader concerns around AI governance, security, and risk. AI is only as good as the data that fuels it, and CDOs must ensure that their AI strategies align with strong data foundations, compliance, and measurable business impact.

One global travel and hospitality company broke the mold when rethinking how customers search and discover offerings. Rather than waiting for AI to reach full maturity, they launched an autonomous AI agent designed to provide real-time answers across web, mobile, and kiosks.

Their approach? Rapid validation over perfection:

• A proof of concept (POC) in just three weeks to demonstrate value
• Early investment secured based on measurable impact
• Immediate business results, including higher conversion rates and order values

This success reinforces a critical AI adoption principle: quick, iterative progress beats long, uncertain roadmaps.

To move from AI theory to execution, CDOs should focus on three key strategies:

• Move fast, but stay precise. AI initiatives must balance speed with governance. The most effective organizations prove AI value in weeks—not months—while ensuring accuracy, security, and compliance.
• Find the “good enough” use cases. AI agents will never be flawless, but that shouldn’t stop adoption. Identify high-confidence, low-risk applications that deliver immediate impact, such as customer service automation, internal knowledge management, and data-driven decision support.
• Treat AI as a capability, not a one-off tool. AI isn’t a stand-alone initiative—it’s a long-term business enabler. The most successful companies embed AI into broader data and technology strategies, ensuring seamless integration with data infrastructure and governance, workforce transformation, and operational processes and business intelligence.

The bottom line: AI success isn’t about perfection—it’s about starting. As one CDO put it, “Just go and start experimenting with AI, even without a fully defined plan. The path will evolve, the innovations will emerge along the way.” The companies that succeed with AI won’t be the ones waiting for perfect models or fully mature solutions. They’ll be the ones that start small, iterate fast, and scale responsibly.

As continuous transformation becomes the norm, CHROs are retooling their workforce to keep pace with rapid changes—not just in AI but across the evolving technology landscape. Forward-thinking leaders are embedding adaptability, critical thinking, and cross-functional collaboration into workforce development strategies to ensure employees can thrive amid constant change. Yet many organizations grapple with how to structure upskilling programs effectively—balancing standardization with job-specific learning, integrating training into daily workflows, and measuring real-world impact.

Our recent CHRO executive forum focused on workforce transformation across three core areas:

• Setting the vision and enrolling key stakeholders: Successful workforce transformation begins with clear project vision, well-defined scope, and strong stakeholder engagement. Survey results revealed that 91% of participants are either building an upskilling strategy or have it on their roadmap, while only 9% are actively executing it. Leaders emphasized that while upskilling is a priority, it must be balanced with other talent development initiatives—requiring careful prioritization and the ability to run concurrent programs without overwhelming teams or slowing progress.
• Building structured and flexible skilling opportunities:  As leaders continue to navigate the pace of change, organizations must take a structured approach to skill development—blending standardized curricula with job-specific applications to ensure employees can effectively integrate new technologies into their work. One executive highlighted that while companies have access to vast online learning resources, the real challenge is applying those learnings effectively in the workplace. Effective upskilling goes beyond AI training—it requires coaching, tailored learning paths, and a focus on applying new skills in real-world scenarios. Leaders are also using upskilling as a way to support succession planning, ensuring employees are prepared for future roles as business needs evolve.
• Developing structured support for measurable outcomes: The success of upskilling programs depends on structured guidelines, early leadership involvement, and a well-planned rollout strategy. Organizations that engage leaders early in the planning process see stronger adoption and smoother integration of upskilling into long-term workforce strategies. For companies with limited learning and development resources, cross-functional roles have been key to scaling efforts effectively. Success is measured not just by participation but by skill validation to ensure employees can apply new knowledge in real-world scenarios. Additionally, many organizations are still refining their approach to compensation, seeking ways to align evolving skill sets with market demand.

While AI remains a key driver, forward-thinking CHROs are prioritizing workforce adaptability as a whole. As transformation accelerates, organizations must build training frameworks that not only address immediate skill gaps but also create a culture of continuous learning and internal mobility to support long-term agility.

For organizations looking to future-proof their workforce, today’s CHROs should ask themselves: What workforce capabilities will be most critical for my organization in the next three years, and how are am I preparing for them?

Success isn’t just about keeping up with AI—it’s about ensuring that people and technology evolve together. By embedding upskilling into business strategy, organizations can create a workforce that’s not only prepared for change but thrives in it.

Marketing leaders today are redefining their role in the C-suite, moving beyond traditional brand ownership to drive measurable business impact. The loosely defined boundaries between CMO, CXO, and CCO are increasingly blurred, making cross-functional collaboration essential. This shift reflects broader industry trends that demand a more integrated and strategic approach to marketing, including a focus on delivering hyper-personalized customer experiences.

Beyond titles, the real challenge is proving marketing’s value. CMOs today face intense scrutiny and pressure to justify every investment, from ROI to technology spend, while balancing broader business expectations. But they can’t tackle this alone. Success depends on collaborating with sales, product, and service teams to align marketing with measurable business outcomes. Without clear ownership of customer experience (CX) and alignment on success metrics, marketing risks being seen as a cost center rather than a growth driver—especially when internal metrics don’t reflect real customer expectations. Many organizations struggle with this disconnect, leading to misalignment and missed opportunities. As one marketing executive put it, “If customer experience is everybody’s job, it’s nobody’s job.“

So what’s next for marketing leaders? 

• Marketing is shifting from function-based to outcome-based leadership. To drive real business value, marketing must be tied to revenue growth, customer retention, and lifetime value—not just awareness and engagement. This requires collaborating closely with sales, product, and customer success to influence the entire customer journey.
• Customer experience must be owned and clearly defined. Organizations need a shared definition of great CX to prevent internal misalignment. This means establishing cross-functional governance where marketing, sales, and service agree on key experience metrics and accountability.
• Marketing leaders must take the lead in proving their business value. The pressure to justify marketing investments is greater than ever, and leaders who fail to connect marketing strategies to measurable outcomes risk being seen as a cost center. Those who embed marketing into business strategy, align with revenue-driving teams, and prioritize customer value will redefine the role’s influence.

The bottom line? Marketing leadership in 2025 is about business impact, cross-functional alignment, and delivering tangible customer value. The leaders who establish clear ownership of customer experience, redefine success metrics, and drive collaboration across teams will be the ones transforming marketing from a support function into a true driver of business growth.

As a COO, your role is to drive operational excellence and efficiency by ensuring that processes, resources, and technology are optimized for scalability, agility, and measurable impact. Yet many COOs are operating with an incomplete picture of how their business actually runs. 

Process mining offers end-to-end operational visibility, revealing inefficiencies and bottlenecks with data-driven precision. Process mining solutions like Celonis can quickly uncover discrepancies between designed workflows, perceived workflows, and actual execution—the so-called spaghetti diagram that shocks many operational leaders. The insights surfaced typically reveal immediate opportunities to drive tangible financial impact, such as identifying missed revenue.

According to research from APQC, “Organizations using process mining over traditional process discovery achieve 25%+ better results in identifying, measuring, and solving business problems.“ This means COOs can identify and unlock measurable cost savings within weeks rather than months or years.

One company used process mining to spot two common, costly mistakes: delivering goods in specific instances without invoicing and payment cycle misalignment that led to working capital leakage. Addressing these saved them £140 million annually in working capital, plus millions more from recovered unbilled revenue. 

Forward-thinking COOs and their teams are leveraging process mining solutions to:

• Uncover deviations: Gain transparency into exceptions, bottlenecks, and inefficiencies that slow operations.
• Prioritize high-impact areas: Focus on the most valuable improvements rather than low-value optimizations.
• Drive evidence-based decision-making: Move beyond intuition to quantifiable process improvements.

The best approach? Start small and expand strategically. Rather than overhauling operations overnight, successful leaders focus on high-value use cases, achieving quick wins, and using the value realized to scale improvements over time. This includes:

• Embedding process mining into daily decision-making through ongoing monitoring and operational control towers to ensure continuous improvement.
• Fostering collaboration and accountability by increasing transparency between teams and aligning process owners, business sponsors, and value engineers through a “three in the box“ approach.
• Addressing multisystem complexity by supplementing process mining with task mining, capturing manual steps and fragmented workflows across different systems.

By treating process mining as a capability, not a onetime initiative, COOs can continuously refine operations, recover lost revenue, and drive long-term efficiencies—ultimately transforming into a data-driven organization that makes decisions with precision and confidence.

CPOs today face a growing challenge: how to empower their teams while ensuring alignment with strategic business goals. At the heart of modern product leadership lies a series of delicate balancing acts—navigating between autonomy and oversight, structure and flexibility, and process and value creation.

In our recent CPO forum, attendees reflected on two key questions that highlight these dynamics: 

1. Empowered teams naturally align with strategic goals if those goals are clearly communicated.

2. Process is the enemy of value creation—if your teams need too many frameworks to make decisions, you’ve already lost.

On the first point, leaders were nearly unanimous—100% of participants agreed or leaned toward agreement. But while clear communication is essential, discussion revealed that alignment doesn’t happen automatically. Teams need more than just a well-articulated vision—they need ongoing reinforcement, a shared understanding of business impact, and the autonomy to make informed decisions. Middle management plays a crucial role in reinforcing strategy, bridging the gap between vision and execution to ensure teams stay focused, remove roadblocks, and make informed decisions.

The second question revealed a divide: 44% leaned agree, 44% leaned disagree, and 13% outright disagreed. The phrase “too many frameworks” in particular sparked debate—while excessive process can slow teams down, many leaders argued that the right level of structure is critical to maintaining alignment, especially as companies scale. Smaller, fast-moving teams may thrive with minimal process, while larger organizations often require more structured decision-making to prevent chaos. 

This debate underscores the critical balancing act for CPOs. Too much structure, and teams lose agility. Too little, and they risk misalignment. In an era where organizations demand both speed and measurable business impact, today’s product leaders must rethink traditional leadership models, moving beyond feature delivery to driving real outcomes.

To ensure teams create genuine strategic value, CPOs must focus on:

• Aligning teams to strategy with continuous reinforcement. Clear goals alone aren’t enough—leaders must create mechanisms for alignment that go beyond communication. This means ensuring teams understand the why behind their work, connecting execution to business objectives, and reinforcing these connections through ongoing discussions, metrics, and cross-functional collaboration.
• Empowering teams with the right level of autonomy and decision-making guardrails. While high performers often advance to leadership, the real challenge is shifting from decision maker to enabler. Effective leaders take responsibility for building environments with clear context and boundaries that allow teams to own outcomes and move quickly without unnecessary approval bottlenecks.
• Navigating uncertainty by creating an environment where experimentation is not just permitted but expected. Cultivating this mindset means actively encouraging teams to take small, low-risk bets rather than requiring complete solutions up front. Celebrating learning from failures—not just successes—builds confidence, reduces organizational risk, and fuels genuine innovation.
• Measuring success by outcomes, not just delivery. Traditional product metrics focus on what gets shipped, but outcome-driven leadership means tying team success to business impact. Whether through customer value, revenue growth, or operational efficiency, leaders must shift performance evaluation to reflect meaningful contributions rather than task completion.

While traditional product leadership prioritized delivery and efficiency, outcome-driven leadership focuses on customer value, strategic alignment, and continuous learning. Embracing this shift starts with self-reflection—where can you step back, provide clearer strategic reinforcement, or create space for experimentation? Small changes in how you lead today can empower teams to drive real impact.

For years, technology leaders have struggled to balance speed, cost, and quality. “Triangulation is normal,” says Sean Everhart, managing director at Slalom. “We typically have to choose two at the expense of the third.” But AI is shifting that dynamic—replacing traditional trade-offs with new possibilities.

In the past, many companies turned to offshore models primarily for cost savings, often separating where products were built from where they were maintained. Today, AI is enabling a more integrated approach—blending highly skilled global talent with automation to drive efficiency, scalability, and speed simultaneously. “The old model was to build in-house and offshore to run it,” Everhart explains. “Now, the question is: How do we create teams that leverage AI at every stage—integrating automation and global talent from the start?”

Chema Ruíz, general manager at Slalom Mexico, reinforced this shift, highlighting how AI is accelerating onboarding, reducing operational friction, and mechanizing tasks that previously required large teams. “Where you may have needed 500 people before, now 50 highly skilled workers leveraging AI and agents can deliver the same impact,” he noted.

CTOs we spoke with echoed this transformation, pointing to AI’s role in global team integration, legacy code modernization, and even cultural adaptation. One technology leader shared the challenge of navigating cultural differences in distributed teams: “AI is not just helping with productivity—it’s helping people work better together.” Another emphasized AI’s growing role in modernizing legacy systems: “AI is changing how we manage older systems, making it easier to transition and consolidate.”

AI is transforming how CTOs think about technology in three key areas:

• Global workforce models. Traditional offshore strategies focused on low-cost labor are giving way to AI-augmented, highly skilled global teams. To adopt AI effectively, CTOs must rethink workforce planning, integrating automation into hiring, team structures, and operational models to drive efficiency at scale.
• AI-driven onboarding and knowledge transfer. AI-powered tools streamline onboarding and reduce knowledge loss, particularly for complex or legacy environments. CTOs should embed AI into their software development life cycle by leveraging automation for documentation, code explanation, and training—reducing ramp-up times and improving team efficiency.
• Cultural and operational alignment. While AI enhances collaboration in global teams, human oversight remains essential. CTOs should prioritize change management strategies that integrate AI tools for translation, communication, and onboarding while ensuring teams remain aligned across different regions and working styles.

AI isn’t just optimizing processes—it’s reshaping how technology organizations are structured, how teams operate, and how software development lifecycles evolve. CTOs who embrace AI-driven workforce strategies can empower global talent, shifting offshore teams from remedial work to AI-enabled contributors who drive efficiency, innovation, and scalability.

CES 2025 showcased groundbreaking advancements in AI, robotics, quantum computing, health tech, sustainable materials, and more. At our recent innovation executive forum, leaders reflected on how these emerging technologies are reshaping industries.

The key challenge for today’s innovation leaders is balancing immediate value creation with long-term disruption readiness. Their focus is on strategic experimentation, cross-industry learning, and change management to drive adoption and competitive advantage. As one leader put it, “We’re a needs-first organization, NOT technology-first. But the speed of AI advancement means that if you don’t adopt, you won’t identify the needs fast enough.” This tension—whether to wait for a clear business case or embrace emerging tech early—is shaping how companies plan for the future.

At the same time, traditional industry boundaries are fading. Leaders across sectors like utilities, healthcare, and finance noted that disruptive technologies are breaking down silos, revealing shared challenges and opportunities. This shift reinforces the value of cross-industry collaboration, where organizations can learn from innovation models outside their own sector.

Yet adopting new technology isn’t just about investment—it’s about people, process, and execution. Across industries, leaders are grappling with how to manage change, educate stakeholders, and ensure that innovation efforts translate into real-world impact.

The key takeaways for innovation leaders?

• Cross-industry collaboration is more valuable than ever. Shared challenges and opportunities mean that organizations can learn from innovation models beyond their own sector.
• Scenario planning helps bridge today’s capabilities with future opportunities. Emerging technologies like AI, quantum computing, and next-gen mobility require phased adoption, starting with today’s practical applications.
• AI adoption requires more than just investment—it requires change management. Leaders must address stakeholder education, workforce upskilling, and risk management to integrate AI effectively.
• A balanced innovation portfolio is critical. Organizations must allocate resources across short-term efficiency gains (Horizon 1), disruptive growth (Horizon 2), and long-term transformation (Horizon 3) to stay competitive.

Leaders know that innovation is only as successful as its adoption. Effective implementation requires more than just investment; it demands change management, education, and alignment. As industry barriers continue to blur, leaders must look beyond their own sectors for insights while staying grounded in their unique business needs and customer expectations. Balancing external inspiration with internal execution will be critical in turning innovation into lasting impact.

The data confirms what sustainability leaders already know: Sustainability isn’t just a responsibility—it’s a strategic profitability driver. Despite economic headwinds and regulatory shifts, the long-term trajectory is clear: Sustainability integration is a business imperative. 

A December survey of 500+ global CFOs revealed strong momentum, with 92% planning to increase sustainability investments, over half indicating significant increases, and 93% seeing a clear business case. Many expect higher ROI from sustainability initiatives than conventional investments. 

However, in our recent sustainability executive forum, 77% of attendees cited competing priorities or misalignment as barriers to integrating sustainability into core business strategy. Many leaders struggle to secure the data necessary to quantify ROI, yet those who do find sustainability investments to be more profitable. Like CMOs advocating for marketing’s role in revenue growth, sustainability leaders must continuously build influence to shift sustainability from a compliance function to a strategic priority.

Another growing concern is whether sustainability teams should focus on regulatory compliance or business growth. Some companies push sustainability into legal teams, treating it as a cost center, but this approach risks missing its full strategic potential. Companies are increasingly leveraging techno-economic analyses to assess the broader ROI of sustainability measures. Rather than viewing compliance solely as a cost burden, many are quantifying the financial benefits of carbon reduction initiatives, balancing the cost of implementation with potential penalties to demonstrate cost savings and long-term value. 

Amid this shifting regulatory and economic landscape, sustainability leaders must focus on building influence across the organization. Without strategic alignment with finance, operations, and product teams, sustainability efforts risk being siloed, limiting their impact on broader business decisions. Leaders who successfully integrate sustainability into core business functions are better positioned to:

• Embed sustainability into financial decision-making. By working closely with CFOs, sustainability teams can ensure investments are tracked alongside traditional business metrics, strengthening the financial case for sustainability.
• Translate sustainability into business value. Moving beyond high-level commitments requires quantifying sustainability’s direct impact on revenue growth, operational efficiency, and risk mitigation.
• Position sustainability as a revenue driver. Companies that advocate for sustainability investments as pathways to innovation and competitive differentiation—not just cost control—unlock new market opportunities.

Looking ahead, leaders who move beyond compliance and embed sustainability into decision-making at every level will be the ones to unlock meaningful impact—delivering both financial returns and long-term competitive advantage.