Growth-focused companies see higher AI ROI

A recent report by the Wharton Human-AI Research (WHAIR) in partnership with GBK Collective found that companies prioritizing growth through AI investments achieve a return on investment three times higher than those focused on efficiency. The study, titled The Adaptive Advantage: Who's Winning with AI and How, surveyed 1,415 American executives and employees to assess AI success across three indicators: delivering value, workflow transformation, and organizational alignment.

Only a few companies meet all AI success criteria

The report shows that only 7% of companies meet all three success indicators for AI adoption. Workflow transformation requires AI integration into key processes, current use of AI, and significant workflow changes. Organizational alignment depends on factors like employee training, clear leadership vision, and the absence of resistance to AI use.

AI adoption is accelerating but with challenges

The report highlights a shift from exploring AI in 2023-2024 to responsible and faster adoption in 2025, with a focus on transitioning from pilot projects to full-scale implementation by 2026. While 80% of organizations report high ROI from AI, the challenge in the coming years may be the gap between those that have transformed workflows using AI and those that have not.

AI is widely used but integration lags

Though 77% of companies use AI agents to perform tasks or execute workflows, only 28% report full integration into their key processes. Just 17% allow AI agents to act autonomously, and only 28% of executives report a clearly positive ROI. Companies that prioritize growth metrics, such as increased sales or production, tend to see better results than those focused on efficiency.

Executives still prioritize cost savings over growth

Most senior executives (52%) view AI’s main purpose as cost reduction, while only 22% see it as a growth driver. Despite 83% of executives expecting AI to transform their industry in the next five years, most still evaluate AI success based on time savings rather than growth indicators like new revenue.

Leadership and structure matter for AI success

Organizations with a dedicated AI director (CAIO) report higher returns on AI investments, with 58% noting strongly positive ROI. Standardizing around a single AI platform also helps, with 50% of companies using one platform reporting very positive ROI. The most advanced sectors, including IT and finance, show the highest returns from AI.

AI adoption changes management and workflow

The use of AI is reshaping management structures, with 37% of companies reporting staff reductions and 33% slowing hiring. However, companies with high AI ROI have not cut staff more than others. Instead, they have modified workflows and focused on monitoring AI use through performance evaluations and training.

Only a small fraction of AI agents are autonomous

Only 17% of companies allow AI agents to be fully autonomous. Most rely on post-hoc reviews or real-time monitoring with safeguards. The report notes that the level of autonomy depends more on risk tolerance than on the agents’ capabilities.

Challenges include security, regulation, and trust

Organizations face obstacles such as data security, regulations, and distrust in AI reasoning. Responsibility for AI errors is a concern, and less than 1% of companies have formal processes to monitor agent performance. Organizational alignment remains a challenge, with less than 40% of companies fully aligned with AI adoption.

Top executives remain wary of AI

A minority of executives (7%) express resistance to AI, fearing job loss and future staff reductions. Despite the growing use of AI, the optimistic view of it has not changed, remaining at 59%. The report notes that AI usage and sentiment are moving in opposite directions, signaling a need for better organizational alignment.

Recommendations for effective AI integration

The report recommends overhauling workflows to fully integrate AI, moving pilot projects into production, and rethinking work management rather than reducing staff. It also calls for monitoring AI usage, providing employee training, granting AI agents authority, and measuring value beyond efficiency. Organizations are advised to appoint a CAIO and adopt a standardized AI platform or formal multi-tool policy.