A recent study by Carruthers and Jackson’s Data Maturity Index indicates that despite the eagerness of companies to leverage artificial intelligence (AI), a significant number struggle to fully incorporate this emerging technology into their operations.
According to the annual poll of data leaders, a staggering 87% report that AI is either used by only a small fraction of their employees or not implemented at all. The survey suggests a prevalent “AI-induced paralysis,” with only 5% of businesses exhibiting a high level of AI maturity, established AI departments, or well-defined AI processes.
Caroline Carruthers, CEO at Carruthers and Jackson, emphasizes that organizations should not despair if they perceive a lack of AI maturity. She underscores that the adoption of any new technology goes through stages of justification, governance, and acceptance, and AI is no exception. Carruthers points out that despite the challenges, data is fundamental to businesses, and organizations are on a collective journey.
To assist organizations in overcoming AI hurdles and building momentum, Carruthers recommends four key priorities for data leaders:
Start with Purpose: Carruthers emphasizes the importance of defining a clear purpose for AI adoption. Identifying the problem to solve, the opportunities, and the objectives sets the foundation for meaningful progress.
Focus on Targeted Outcomes: Instead of tackling grand challenges, organizations are advised to concentrate on smaller, manageable problems where AI can make a tangible impact. This targeted approach allows for gradual and effective implementation.
Shout About Successes: Carruthers encourages data leaders to communicate their achievements openly. Celebrating successes helps build support and encourages others to join the journey toward AI adoption.
Use Data to Prove Your Case: Demonstrating tangible results from AI projects is crucial. By showcasing the positive outcomes and metrics achieved, organizations can gain buy-in for future AI initiatives.
Despite the excitement surrounding AI, Carruthers identifies two significant hurdles hindering its widespread adoption: people and regulations.
People Problem: Overcoming resistance from all levels of employees, from the boardroom to the shop floor, is a crucial aspect of successful AI implementation. Carruthers acknowledges the challenge of convincing people, who often associate AI with job loss and potential workforce impact.
Regulatory Bind: Concerns about data ethics and anticipated stringent data laws create a regulatory bind for executives. With unclear legislation on the horizon, many companies are cautious about diving headfirst into AI.
The research suggests that a combination of a wary workforce and uncertainty regarding regulations has left many organizations at the starting gate of AI adoption. Pilot projects and foundational elements, such as data frameworks and strategies, are limited in these circumstances.
Approximately 41% of data leaders reported having little or no data governance framework, a slight increase from the previous year. Moreover, 27% stated that their organization lacks a data strategy. Carruthers underscores the importance of focusing on governance and strategy to prepare for AI exploitation effectively.
While challenges persist, some digital leaders are making progress. Andy Moore, CDO at Bentley Motors, emphasizes the necessity of laying the foundations for emerging technologies. He outlines a comprehensive strategy encompassing governance, the data cloud, internal data literacy programs, and enablement to support the data team in collaboration with the wider business.
As organizations navigate the complexities of AI adoption, balancing expectations and establishing robust foundations emerges as a critical task for data leaders moving toward data-led goals.