Why Most Companies Are Still Struggling to Unlock Generative AI's Business Value

The race to adopt generative AI is accelerating, yet most organizations remain stuck in the exploration phase while their competitors potentially gain ground. A new Harvard Business Review study reveals a striking disconnect: 83% of executives believe companies that don't embrace gen AI will get left behind, but only 48% say their organizations are actually ready to adopt it.

The Readiness Reality Check

Despite the urgent need to act, organizations face significant preparedness gaps across critical areas:

• Skills and knowledge deficits – Most employees lack the training to effectively use gen AI tools
• Risk management concerns – 56% cite potential ethical, legal, and cybersecurity risks as the top barrier
• Missing roadmaps – Half of organizations lack clear implementation strategies

According to Goldman Sachs forecasts, gen AI could drive a $7 trillion increase in global GDP over the next decade, making the stakes for early adoption particularly high.

How Leading Companies Are Breaking Through

Organizations seeing real results are taking deliberate steps to address these challenges:

Eversana, a pharmaceutical services company, credits its success to comprehensive change management. "Gen AI is probably the biggest technology shift we've seen in our lifetime—at least as big as the internet," says Abid Rahman, senior vice president of innovation. The company established clear guidelines and ongoing training programs that helped employees quickly improve their gen AI capabilities.

Restworld, an Italian hospitality recruitment platform, achieved approximately 20% cost savings by using gen AI to handle initial candidate conversations via WhatsApp, freeing recruiters to focus on higher-value analytics work.

Canva has generated over 1.2 billion images using its Magic Design feature, demonstrating how gen AI can become integral to customer workflows rather than just a novelty tool.

The Key Success Factors

The most successful implementations share common elements:

• Executive commitment – Leadership drives adoption from the top down with proper investment
• Rapid iteration – Building feedback loops to test, refine, and improve gen AI applications quickly
• Human oversight – Maintaining quality control through human verification of gen AI outputs

Organizations that view gen AI as merely an efficiency tool miss its transformative potential. The real opportunity lies in fundamentally rethinking work processes and business models to fully leverage this technology's capabilities.

Read the full report on Harvard Business Review