In December of 2024, the IBM Institute for Business Value (IBV) released “5 Trends for 2025” a report that examined how business leaders can empower people to innovate in the age of AI without putting the business at risk. “2024 was a year of letting go,” said the report in its Introduction. “As a combination of conflict and transformation threw old assumptions into doubt, leaders had to reassess their appetite for risk. They had to weigh the need for speed against the safety of proven processes — then change the habits that were holding them back.”
“Generative AI was at the center of this shift, introducing a world of new opportunities, as well as uncharted risks,” the report added. “Agentic AI, which refers to systems and programs that perform a variety of functions autonomously, can act on behalf of employees while they do other work. By giving AI agents specific permissions and rights, they can automate decision-making, problem-solving, and other tasks that go beyond the data the system’s machine learning models were trained on in a way that most AI assistants don’t. And as digital labor evolves, it puts the power of transformation firmly in employee’s hands. It makes it possible for individuals to increase productivity and redefine workflows — and challenges preconceived notions about what it means to lead.”
In this environment, business leaders are walking a tightrope between agility and security. To learn how they’re doing it, IBM’s Institute for Business Value conducted a survey of 400 global leaders across 17 industries and six geographies in October and November of 2024 in partnership with Oxford Economics. Participants were asked a number of questions about their business and technology strategies, their most promising opportunities, and how they’re preparing their workforce to take advantage of these changes.
Introduction: AI democratizes data — and redefines decision-making
How can leaders empower people to innovate without putting the business at risk?
Overall, leaders are struggling to transform the business with their AI investments but believe that they’re making progress. 63% of executives said that AI will have a material financial impact on their organization in the next one to two years.
In 2024, 30% of executives said that their organizations were primarily experimenting with AI in low risk, non-core functions, 44% were using AI to optimize existing processes, and only 24% were trying to use AI to uncover innovative new opportunities and business models. But in 2025, those same leaders expect to see a major shift. Only 6% say that their organizations will still be primarily experimenting with AI, 46% said that they’ll be scaling the use of AI across their enterprise, and 44% expect to use AI to innovate.
“Getting it right can help companies stay ahead of the competition and strengthen customer relationships.” Let me summarize the five key AI trends discussed in the report.
Trend 1: Agentic AI will transform your business — but first you must reskill your people
The future of work is being rewritten with AI. But many employees are unprepared for what comes next — and progress will stall if too many are left behind.
“While roughly 5% of the global workforce consistently needs to be reskilled each year, the rapid evolution of AI has sent this figure skyrocketing. In 2024, global CEOs estimated that, on average, 35% of their workforce needed to be reskilled. That translates to more than a billion workers worldwide.”
“What exactly is creating this chasm? The escalating need for true transformation. Instead of automating specific roles wholesale, organizations are pairing people with domain-specific AI agents to improve their performance. In fact, 87% of executives expect jobs to be augmented rather than replaced by generative AI. This means, rather than learning a new skill or tool, workers must completely rethink how they do their jobs to make the most of gen AI.”
Trend 2: Despite efforts to slow its growth, technical debt continues to increase
Time is money. And leaders are always looking for ways to save both. But the workarounds that accelerate transformation in the short term often create technical debt that limits long-term innovation and growth.
“To deliver the innovations that customers, employees, and partners expect, organizations must build solutions within a modern architecture. That’s because traditional systems don’t tend to play well with next-gen apps, software, and infrastructure. This is particularly relevant for generative AI and agentic AI. Organizations need robust infrastructure that can handle the data and computational requirements of AI to go from pilots to enterprise-wide solutions. Yet, while 77% of executives say they need to adopt gen AI quickly to keep up with competitors — only 25% strongly agree that their organization’s IT infrastructure can support scaling AI across the enterprise.”
Trend 3: In the age of AI, location is everything
Perpetual disruption is here to stay. But that doesn’t mean it’s predictable. To navigate complexity wherever it rears its head, leaders must be able to see the big picture — and the market-level minutiae — in one sweeping view. They must strategically adjust operations based on market-level shifts, without overreacting to local disruptions as they occur.
“And striking the right balance is getting harder every day. Looking to the future, 60% of government leaders believe that shocks are likely to increase in frequency and 70% believe they’re likely to increase in intensity and impact. This is forcing business leaders to assess where their data is housed and rethink how, — and where, — their organizations should operate. In 2024, 86% of executives said their location strategy was impacted by geopolitical disruption — and that figure is expected to rise to 93% in 2026. As organizations seek out the talent, data ecosystems, and infrastructure needed to scale AI effectively, they’re moving operations to places they believe will provide the greatest strategic advantage.”
Trend 4: The rapid pivot to AI has upended IT budgets, but self-funding is imminent
95% of executives say gen AI will be at least partially self-funded by 2026. Generative AI has made the traditional IT budgeting process untenable. It’s sending shockwaves through technology and finance teams as they rush to reevaluate their spending priorities — and move money where it’s needed most.
“Leaders know they need to invest in gen AI to keep up with the competition, but these solutions have yet to deliver production-level ROI. This has led to widespread cannibalism of broader IT budgets. In 2024, one in three organizations pulled funding for gen AI from other IT initiatives, with only 18% of tech execs funding these projects with net-new spend. … Nearly all executives (95%) say gen AI will be at least partially self-funded by 2026, with a focus on driving future profitability. While three in four business leaders are thinking of gen AI more like an innovation investment than traditional IT today, 71% of executives say gen AI should be self-funded to justify its investment.”
Trend 5: AI product and service innovation is the #1 CEO goal, yet business models aren’t keeping up
As generative AI supercharges innovation, the pipeline of new products and services is bursting at the seams. But many organizations are too wedded to old business models to tap into new opportunities to drive growth.
“CEOs are feeling the crunch. In 2024, they cited business model innovation as the top challenge they expect to face over the next three years—up from 10th place in 2023 — while also naming product and service innovation as their top priority for the same timeframe. Business leaders understand that, to make the most of innovative offerings, they’ll also need to rethink how they turn a profit.”
“In fact, 62% of CEOs say they must rewrite their organizational playbook to win in the future. AI will play a major role in this shift. Over the next three years, 85% of executives say AI will enable business model innovation and 89% say it will drive product and service innovation.”
“What does this look like? It starts with analyzing customer and market data faster and more comprehensively than ever before — then changing strategies to keep up with shifting demands. This will require centering business models on the careful design of human-machine interaction — and building strong supporting governance structures—as well as rethinking organizational structures and workflows.”