Returns on genAI initiatives pick up; patience and employee training remain critical

The news: Companies are starting to see returns on their generative AI (genAI) initiatives, though hurdles still challenge widespread market adoption.

• Returns on investment (ROI) for advanced genAI initiatives are meeting or exceeding expectations at 74% of US organizations, per Deloitte’s Q4 State of GenAI in the Enterprise report.
• However, 35% of organizations say marketplace adoption could be slowed down by real-world consequences from genAI mistakes, and 29% say potential loss of trust due to biases and inaccuracies is the top risk to mass adoption.

Growing pains: While many organizations are meeting ROI and integration goals for genAI applications, this will take a little longer for others.

70% of organizations say it will take at least 12 more months to resolve adoption challenges and hit expected ROI, and 76% are willing to wait that long before starting to reduce investment in underperforming projects.

That patience could help change previous stats on project abandonment: In August, Gartner predicted at least 30% of genAI projects would be abandoned by the end of this year due to unclear paths to profitability.

Deployment plans: Companies are deploying genAI for a variety of use cases.

• GenAI’s coding abilities have led to IT being one of the most targeted departments for AI initiatives, ranking at 28%, per Deloitte.
• Companies are also focused on advanced initiatives in marketing (10%) and customer service (8%).
• Agentic AI is one of the most interesting areas of genAI application for companies, with 52% saying that automation is their organization’s top interest.

Lingering hurdles: Limited access to the tech for about two-fifths of workers, and low daily use for those with access, could slow widespread adoption.

• Less than 40% of the workforce has access to genAI, and less than 60% of those employees engage with it daily.
• Opportunities are even more limited for female employees—only 29% of AI-skilled workers are women, per Randstad.

Our take: A lack of solid use cases could make it harder to justify widespread genAI adoption, creating a cycle of stagnation.

Companies need to balance executives’ enthusiasm for genAI with market interest. Putting money and resources into genAI applications that have little consumer interest—like customer service—and failing to train employees will dampen ROI for these projects.

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