These five strategies can help you generate faster returns on your AI investments
While top business leaders are increasingly investing in AI and other advanced technologies, many are not seeing anticipated returns. In fact, a survey published in May 2025 by the IBM Institute for Business Value found that only 25% of AI initiatives have delivered expected ROI over the last few years.
This is not surprising among those who have seen their share of tech implementations. Organizations have long struggled to add and integrate the most advantageous new platforms without losing time, momentum, and often market share. Among adoptions that do come in on time and on budget, relatively few yield the intended big-picture results.
Integration lapses
This reflects the tendency of leaders to separate their IT and people needs into separate categories when tech adoptions require them to focus on both simultaneously. Even the most forward-thinking executives who invest in robust change management often completely delegate this responsibility, detaching themselves from their people's implementation experiences.
These lapses are becoming increasingly hazardous as individuals across generations internalize adverse views of AI and even act on them in alarming ways. For example, a March 2025 study by generative AI platform Writer found that 31% of employees—including 41% of Gen Z workers—admit to 'sabotaging' their company's AI strategy by refusing to adopt AI. As a result, roughly two-thirds of executives say adoption efforts have led to tension and division within their organization, with 42% suggesting it's 'tearing their company apart.'
New perspective
To fully harness the power of today's most innovative tools, leaders must adjust the lens through which they view technology and recognize the outsized influence their people will have before, during, and after implementation processes. This shift in thinking will make it possible for them to fully embrace proven, though underutilized, people-first tech adoption strategies that help drive meaningful returns.
These strategies include:
1. Meet your people where they are
While top leaders spend extensive time and energy contemplating the wisdom of changes before driving them forward, their people are granted little such runway. Intellectually and emotionally, they're playing catch up, and thus require patience on the part of leaders as well as highly tailored communication and direction that creates and enhances alignment.
2. Emphasize the 'why'
To help team members believe, comprehend, and appreciate the rationale behind AI and other tech implementations, leaders should deliver a compelling, authentic, consistent narrative. Done well, such effort will help employees understand the all-important 'why,' a key first step toward internalizing, accepting, and fully utilizing new technologies.
3. Consider systemic impact
While some technologies lead to groundbreaking efficiencies, many create new, unforeseen challenges, especially at the people level. Organizations should be proactive about identifying such risks, addressing potential and emerging issues through a variety of tools, from workstream design to communications and training.
4. Foster change agility
The AI technology of even six months ago is very different from today, and will be different again in another six months, necessitating that leaders prepare their organizations for future and ongoing tech adoptions. This will require companies to shed legacy cultures of change resistance in favor of change agility—efforts that are especially important in historically change-adverse industries, like healthcare.
5. Stay focused on leading
With countless competing priorities, it's tempting for top leaders to delegate their organizations' tech implementation efforts. Yet the gravity of today's AI evolution requires their active participation and leadership across all stages of the adoption work, from shaping the narrative to outlining critical success factors, to communicating the importance of the change.
Keeping ahead
Fundamentally, today's AI era is as rooted in people issues as it is in technology issues, necessitating human capital-oriented approaches. Leaders that internalize this reality can best harness the power of novel technologies as a means of driving transformational, profitable, and sustainable improvements, staying ahead of the competition and generating returns on AI investments.
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