As AI adoption expands globally, board members and senior leaders are defining how to manage and govern the human + AI partnership to maximize their return on investment. They report key learnings.
01
As early as 2019, Professor Mark Kennedy of Imperial College London distinguished between the role of AI in automation (replacing human tasks with technology), augmentation (improving human outcomes through technology) and addition (finding new sources of value).
Many early AI adopters report success comes from a combination of cost reduction through automation, increased quality through augmentation and competitive differentiation through addition. As AI becomes more mainstream, effective leaders move beyond solely using it for cost savings and productivity to expanding human capability through augmentation and addition. This drives organizational differentiation through deeper thinking, more innovation and research and development, new ways of connecting with customers, enhanced products and services, and superior user experience.
02
A new study quantifies what many board members and senior leaders have reported about the cost of adopting and scaling AI. The February 2026 study, published by Tatsuru Kikuchi at the University of Tokyo, suggests an AI “implementation tax,” where banks experience a 428 basis-point decline in return on equity (ROE) as they absorb generative AI integration costs. The impact varies considerably by organization size, from a 517 basis-point ROE decline for the smallest organizations to 129 points for the largest. The study also cites research on the “productivity paradox,” documenting that the classic J-curve pattern of technology adoption also applies to generative AI. This helps explain the low ROI of early AI adoption reported by numerous recent studies.
Effective leaders consider timing, investment levels and expected ROI when making AI adoption decisions. They also set reasonable expectations with key stakeholders.
03
Recently, during a discussion in Palo Alto, CA, with Ramneek Gupta, founder and managing partner of PruVen Capital, and his team describe one of his firm’s 2026 “MetaTruths” as, “AI does the ordinary so humans can do the extraordinary.” PruVen suggests adopting AI to handle routine processes and analytics, while humans focus on exercising taste, judgment, discernment, building relationships and emotional connections.
In February’s Fast Company, Pete Pachal, founder and CEO of The Media Copilot, explains that AI separates routine writing from the work that defines reporting, including building trust with sources, doggedly pursuing leads, assessing crime scenes, attending hearings, judging credibility, drawing inferences without full facts, and inspiring and engaging audiences with novel thought and storytelling.
A similar pattern appears in corporate call centers, where leaders find that AI handles routine tasks, such as retrieving information and filling out forms, freeing representatives to focus on customer relationships and solve more complex problems on the first try. Effective leaders understand and employ the power of AI to shift worker value from ordinary to extraordinary wherever possible.
04
There is broad agreement among board members, senior executives and tech experts that AI eventually will replace some jobs or require fewer traditional roles. Substantial debate centers around how many new jobs AI will create, as occurred during past technological “revolutions.” To inform this debate, effective leaders look to research and reports on new jobs that already exist among AI adopters.
For example, WTW’s 2025 Artificial Intelligence and Digital Talent Intelligence Report finds that the top five most in-demand digital skill roles globally are software engineer, application developer, data scientist, test engineer and cybersecurity engineer. Newer roles such as full-stack developer, solution architect, machine learning engineer, data engineer, cloud engineer and AI engineer appear in the top 20. AI adopters also report the appearance of roles such as AI ethicist, virtual cultural architect, AI automation engineer and robot trainer. Effective leaders understand these roles may change or fade as AI develops but are needed today and provide a lens into future skill requirements and job opportunities.
05
Many board members and senior leaders report more successful AI adoption when organizations build critical skills through upskilling, reskilling and hiring. They also report the need to define “adoption” beyond metrics such as user licenses or occasional users.
WTW’s 2025 Talent Market Trends Dashboard shows that emerging skills vary by industry and geography. For example, in some places, data storytelling, predictive analytics and data visualization represent top emerging skills. In others, the focus is on prompt engineering, data governance management, cyber threat management, risk modeling and demand generation. As previously reported, effective leaders understand that soft skills are as important as hard skills. Critical and analytical thinking, creative thinking, problem solving, judgment, emotional intelligence, resilience, empathetic leadership and self-awareness are crucial as AI technology advances.
06
Board members and senior leaders have learned that reimagining the processes in which AI is applied is necessary to achieve desired goals. Rather than engage in a “humans versus AI” debate, effective leaders rethink processes with a “best of” approach, considering which processes are best served by AI, humans or, most frequently, both. They recognize that AI tools and agents perform well on discrete tasks, but not entire processes, though the agentic web may change this. The most successful implementations start with point solutions that are woven together to form effective, broader processes once the technology, skills and learning have meaningfully advanced.
07
PruVen stresses that “society values authentic human experiences in a world of AI slop.” WTW’s Jorge Coelho, Jill Havely and Richard Veal wrote about employee value propositions that can survive the AI revolution, where the value of human-to-human interaction persists. Moments of empathy, recognition and connection define the employee experience in an increasingly digital world.
Effective leaders use AI to reduce routine tasks and augment managers’ ability to activate extraordinary leadership. They point to cultures of purpose and learning as critical, particularly as models and daily operations transform and where employees fear obsolescence. The most effective leaders create extraordinary engagement by routinely communicating and telling stories about changes, listening to employee concerns and responding appropriately.
WTW’s Suzanne McAndrew shares humans make AI better and AI makes humans better. Today, effective leaders embrace the human + AI partnership to create the extraordinary.
A version of this article originally appeared on Forbes on March 12, 2026.
An organization’s employee value proposition must be able to change fast enough to remain relevant amid rapid technological and societal change.
