AI Publications

🔗https://shre.ink/Wharton-GenAI-adoption-into-the-Enterprise

1. Context

The report arrives at a pivotal moment: After years of experimentation and hype around generative AI (Gen AI), enterprises are now moving into the deployment and value-capture phase.

The study’s authors note that organizations are no longer just testing tools—they are integrating Gen AI into core workflows, scaling up investment, tracking returns, and facing the real challenge of aligning people, processes and trust. In this sense, the report positions 2025 as the year of “accountable acceleration” rather than mere promise.

2. Study Objectives and Methodology

The core goals of the research were to take the pulse of enterprise Gen AI adoption—building on Wharton’s prior waves in 2023 and 2024—and to focus on usage, perception, investment, governance and human-capital dimensions.

The methodology: a survey of U.S.-based commercial organisations with 1,000+ employees and > US$50 m revenue, across functions (Marketing/Sales, Operations, Product/Engineering, Procurement, Finance/Accounting, General Management).

3. Tracking the Rapid Acceleration of Gen AI in the Enterprise

The data shows that Gen AI usage is becoming mainstream. For example, 37% of organisations reported using Gen AI at least weekly—a meaningful jump.

Moreover, daily use is growing across functional areas, especially in IT and Procurement, though there remains variation across industries and company sizes. The study also highlights that while larger enterprises (Tier 1) are ramping up, smaller and mid-sized firms (Tier 2/3) are often more agile and showing steeper adoption gains.

4. Accountable Acceleration: Gen AI Fast-Tracks Into the Enterprise

There are three themes by which organisations are converting Gen AI potential into value: Everyday AI, Proving Value, and The Human Capital Lever.

4.1 Everyday AI: Usage Is Now Mainstream

The “everyday” part means that Gen AI is no longer a niche pilot but now part of regular workflows. Functions like IT, Procurement, Operations report high levels of usage and confidence.

However, gaps persist—for example Marketing/Sales and Management functions lag somewhat in frequency and expertise. The report warns that this unevenness could widen the divide between “AI-enabled” and “AI-laggard” organisations.

4.2 Proving Value: Measuring Investment, Impact & ROI

A key shift: organisations are moving from “explore and experiment” to “invest and measure.” Approximately 72% of business leaders now track structured ROI metrics (profitability, throughput, productivity) for Gen AI initiatives.

Most report positive returns already, and many see the next two to three years as crucial for scale. Budget discipline shows up—some are reallocating from legacy IT or HR to Gen AI.

4.3 The Human Capital Lever: Aligning Talent, Training & Trust

The report emphasises that technology alone doesn’t guarantee value—people do. As Gen AI becomes embedded, organisational readiness matters: leadership ownership, training, employee trust, governance.

For example, 60% of surveyed firms now have a Chief AI Officer (CAIO) or equivalent role. At the same time, concerns persist: skill gaps, uneven training, scepticism among mid-managers, and the risk that proficiency may decline for some workers as automation expands.