The Challenges Faced by U.K. Businesses in Implementing AI Projects
AI technology has been heralded as a game-changer for businesses across various industries. However, a recent study conducted by data management platform Qlik has revealed that many U.K. businesses are struggling to get their AI projects off the ground.
Data Governance as a Key Challenge
The research found that 11% of U.K. businesses have numerous AI projects stuck in the planning stage, while 20% have experienced projects that had to be paused or canceled. According to James Fisher, Qlik’s chief strategy officer, one of the main reasons for these failures is the lack of proper data governance.
Fisher explained, “AI projects can fail to deliver when there is a lack of high-quality, structured data or when objectives are ambiguous. Without a solid data strategy, AI models struggle to provide meaningful insights.”
Implementing an AI strategy incorrectly can have disastrous consequences, as evidenced by past failures in the industry. Lack of trust in AI among senior managers, exacerbated by high-profile failures like Air Canada’s chatbot incident, further complicates the adoption of AI technology.
Seeking Plug-and-Play Solutions
Gartner estimates that building custom AI models can be costly, ranging from $5 million to $20 million. In light of these expenses, Fisher recommends seeking out “plug-and-play” AI solutions that offer a more cost-effective and sustainable alternative.
He advised business leaders to start with smaller AI projects to demonstrate proof-of-concept before scaling up. Establishing a strong data foundation, clear business objectives, and regular ROI assessments are essential steps to ensure the success of AI initiatives.
By focusing on purpose-driven models and targeted applications, businesses can mitigate risks associated with AI implementation while reaping the benefits it offers. Fisher emphasized the importance of knowledge sharing and upskilling across the organization to build trust in AI technology.
Overall, a gradual approach to AI adoption, coupled with a focus on measurable outcomes and continuous evaluation, can help businesses overcome the challenges associated with AI projects and harness the full potential of artificial intelligence.