GenAI in the Enterprise: From Hype to Human Capital

Generative AI has rapidly shifted from experimentation to everyday utility in large enterprises. In the final installment of our Fall 2025 AI Horizons webinar series, Wharton Human-AI Research Faculty Co-Directors Stefano Puntoni and Prasanna (Sonny) Tambe joined Jeremy Korst, Partner at GBK Collective, to share findings from the 2025 AI Adoption Report: GenAI Fast-Tracks into the Enterprise. Here are the key takeaways from their talk.

Daily Use Is Now a Competency Marker

Across three years of surveying senior leaders, daily GenAI use has climbed sharply:

• 2023: ~10% of executives used GenAI daily
• 2025: Nearly 50% now do

Puntoni notes that “daily use at scale signals GenAI has moved from a novelty to a tool leaders rely on.”

Adoption differs by function. IT remains the most mature, while marketing, despite clear value potential, has plateaued despite early rapid uptake. Leaders attribute this to transformation fatigue and uncertainty about how GenAI reshapes roles.

For organizations, this shift signals something bigger: daily GenAI use is becoming an indicator of functional fluency. Functions that stall may fall behind even when their work is well aligned with GenAI’s strengths.

Productivity Gains Continue, Creativity Surges

The most mature enterprise use cases remain the horizontal activities that anchor modern knowledge work:

• Data analysis
• Document and meeting summarization
• Editing, writing, and proposal development
• Presentation and report creation

But the biggest year-over-year growth comes from idea generation and brainstorming, a use case cited by more than 60% of organizations. Leaders see this as the transition from “GenAI as a productivity engine” to “GenAI as a creativity accelerator.”

Customer-facing and employee-facing workflows are also increasingly augmented: marketing content creation, sales enablement, customer support chatbots, and internal help-desk automation all rank among the top use cases.

ROI: Strong Early Signals, Even as Measurement Matures

This year marks the first time the report explicitly asked leaders whether they measure ROI on GenAI. Over 70% say they now do formally or consistently.

Among organizations that measure:

• 3 in 4 enterprise leaders report positive ROI
• Few report neutral or negative outcomes
• Many still say it is “too early to tell”

Smaller organizations report more positive ROI, while large enterprises face measurement challenges tied to governance, complexity, and slower adoption cycles.

The takeaway: hard metrics matter, but early wins and organizational confidence are shaping budgets and roadmaps.

Human Capital Is Now the Central Challenge

The focus of GenAI adoption has shifted decisively from technology to people, skills, and organizational design.

1. GenAI Is Viewed as a Skill Enhancer

Roughly 90% of leaders say GenAI enhances employee skills. Fears of job displacement have not increased, reflecting growing recognition of human–AI complementarity.

2. Skill Decay Is an Emerging Risk

About 43% worry GenAI may weaken core capabilities such as writing, analysis, and critical thinking. Junior employees may fail to acquire foundational learning if AI is always present. Firms may need deliberate strategies, akin to pilots practicing manual flying, to maintain proficiency.

3. Talent Pipelines Are Shifting

Organizations report difficulty recruiting employees with advanced GenAI skills and are investing heavily in upskilling. Leaders do not expect fewer entry-level roles but rather anticipate greater demand for AI-native early-career talent, especially interns who surface new use cases. Hiring is also adapting with more in-person assessments and longer interviews as work samples become harder to interpret in a GenAI era.

Leadership, the “Messy Middle,” and the Rise of the CAIO

A widening perception gap is emerging:

• Executives are optimistic and focused on strategic opportunity.
• Middle managers face the operational friction—workflow redesign, morale management, and change adoption.

Korst warns that neglecting this “messy middle” can slow progress.

Governance structures are evolving quickly: nearly 60% of organizations now report having a Chief AI Officer or equivalent. Tambe adds that sentiment matters because “the vibe affects investment,” underscoring how organizational confidence shapes both budgeting and momentum. Korst notes that CAIOs succeed when they bridge technology and business, positioning AI as a driver of enablement rather than an isolated technical domain. To visit the rest of our AI Horizons webinars from this fall, click here.