AI Maturity in 2024

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Mar 14

Do you know what a compound annual growth rate (CAGR) of 42% gets you over 10 years? It takes you from $40 billion to roughly $1.3 trillion, the forecasted market size for Generative AI by 2032 according to Bloomberg Intelligence.

Developed in 2018, Gartner’s AI Maturity Model has helped many companies identify where they currently stand and how they compare on the potential growth curve. This graphic shows data combined from 3 different sources: Gartner, LXT, and MorphL (Acquired by Algolia) to help illustrate a path for AI maturity, the gaps, and where the industry currently stands.

According to LXT’s Path to AI Maturity report, we are seeing a significant shift: a 24% increase in companies advancing from Experimenters to Maturing stages, indicating a deeper, more operational integration of AI technologies. The spotlight on generative AI has revealed both its potential and current challenges. Despite its critical importance, 69% of enterprises prioritize it over other AI initiatives: its deployment and ROI lag, reflecting the nascent state of this transformative tech.

Interesting trends emerge from this shift: AI's role in risk management has overtaken business agility as the primary driver, while search engines and predictive analytics lead in deployment and ROI. This evolving landscape underscores the necessity of strategic AI investment and the ongoing need for high-quality training data to fuel future innovations.

How to Improve Your AI Maturity

Blend AI and Data Strategies with Your Business Goals Don’t let your AI and data strategies float on their own. Integrate them into your overall business strategy. This ensures AI projects align with your core objectives, whether it's boosting customer experience, optimizing operations, or sparking innovation. Keep your data quality top-notch and make sure everyone understands how AI drives your business forward.
Make AI Everyone’s Business AI should be a priority for the whole organization, not just the IT department. Get executive backing and clearly communicate AI’s importance. Develop a roadmap showing how AI will impact different functions and encourage collaboration across teams. Allocate the necessary resources to ensure AI projects are well-supported.
Foster an AI-Friendly Culture Create a culture that embraces AI by educating employees on its benefits and addressing any concerns. Offer training to build AI skills and reward teams that successfully implement AI. Encourage experimentation and make it easy for employees to test and iterate AI solutions.
Hire and Develop the Right Talent To get the most out of AI, you need the right people. This includes data scientists, machine learning engineers, and AI ethicists. Focus on recruiting top talent, offering competitive pay, and providing continuous learning opportunities. Partner with academic institutions and AI research organizations to stay on the cutting edge.
Set Up an AI Ethics Committee Ensure AI is used responsibly by establishing an AI ethics committee. This group should include diverse perspectives and oversee the development and deployment of AI technologies. Create policies to address issues like bias and transparency, and regularly audit AI systems to mitigate risks.
Standardize and Share Best Practices Standardize how AI models are built, deployed, and monitored. Develop best practices and templates for consistency and reliability. Implement robust MLOps (Machine Learning Operations) practices to streamline AI model management. Encourage knowledge sharing and document AI project experiences to continuously improve.

By focusing on these six key areas, you can enhance your AI maturity and position your company for success in an AI-driven world.