The AI Maturity Gap Insights from Kearney's 2024 Global AI Assessment
The age of AI is here, and businesses are racing to adapt. Investment is pouring in, and the promise of transformation is on every CEO's lips. Yet, a stark reality emerges from Kearney's research: while nearly every company is on the journey, a massive gap separates the ambitious majority from the elite few who have achieved true AI maturity. This is the story of that divide.
The Great Divide: AI Maturity Is Rare
Kearney's research categorizes companies into four distinct stages of AI and analytics maturity. The findings reveal a striking imbalance, with over half of all organizations still possessing immature capabilities, struggling to build and scale their AI initiatives effectively.
Leaders (4%)
Pioneers with advanced, integrated AI capabilities that drive significant business impact.
Explorers (45%)
Making progress with well-defined goals but still developing their full potential.
Followers (47%)
Have strategies but struggle with execution, scale, and governance.
Laggards (4%)
Lack defined goals, funding, and clear governance for AI initiatives.
Why Maturity Matters: The Leader's Advantage
AI Leaders aren't just slightly ahead; they operate on a different level. Their commitment is reflected in significantly higher investment, robust governance, and strong executive sponsorship, creating a powerful flywheel for innovation and growth that leaves Laggards far behind.
The Generative AI Wave: Promise and Pitfalls
Generative AI has captured the world's attention and budget. While a vast majority of organizations predict it will drive revenue, significant hurdles—especially a lack of technical expertise—are preventing widespread, effective adoption.
of organizations predict GenAI will inspire revenue growth.
of the total data & analytics budget is now allocated to GenAI.
Top Barrier to Adoption
A lack of technical expertise is the most cited hurdle.
Kearney's Blueprint for AI Maturity
Closing the maturity gap requires more than just technology; it demands a fundamental shift in culture, strategy, and operations. Kearney outlines a clear path forward for organizations aiming to transition from followers to leaders.
1. Foster a Culture of Experimentation
Embrace a "fail fast, fail cheap, fail forward" mindset. True innovation in AI requires giving teams the space to experiment and learn without the fear of failure. A culture that values continuous learning is essential for delivering sustained business value.
2. Treat Data as a Core Business Asset
Clean, accessible, and well-governed data is the bedrock of any successful AI initiative. To unlock its full value, organizations must break down data silos and ensure that high-quality data is available for all teams to use and drive insights.
3. Evolve the Operating Model
An AI-powered world demands a new way of working. It's a game of "AI + Human Intelligence," where technology augments human capabilities, not replaces them. This requires redesigning workflows and providing the training needed for people to leverage data effectively.
4. Invest in People
Ultimately, people are the engine that leverages the power of AI. Organizations must focus on hiring strong talent, incentivizing them with performance-linked rewards, and managing their career growth to minimize attrition and build long-term institutional knowledge.
Yong Xu
Detailed Research Report
