Companies Rush to Adopt AI, but Results are Elusive, KPMG Executive Says
A recent report from KPMG found that companies are struggling to prove the effectiveness of their AI strategies, highlighting a disconnect between adoption and actual results. This disparity matters because it can impact the competitiveness and bottom line of businesses. Mathieu Wallich-Petit, Head of Clients & Markets at KPMG France, shares his insights on the state of AI adoption in business.
Companies May Have AI Strategies, but Few Can Prove They're Paying Off
Euronews Next spoke with Mathieu Wallich-Petit, Head of Clients & Markets at KPMG France, about the state of AI adoption in business. According to a recent report from KPMG, companies are rushing to adopt AI, but few are able to prove that their strategies are paying off. The report found that only 12% of companies have achieved significant benefits from their AI investments. This is a worrying trend, as businesses are investing heavily in AI, with the global AI market expected to reach $190 billion by 2025. Account to Euronews Next, Wallich-Petit noted that companies are struggling to measure the effectiveness of their AI strategies, with many relying on anecdotal evidence rather than hard data.
The Disconnect Between Adoption and Results
The disconnect between AI adoption and results is a complex issue with far-reaching consequences. On one hand, companies are investing heavily in AI, hoping to gain a competitive edge. On the other hand, few are able to prove that their strategies are paying off. This can lead to a lack of trust in AI, as businesses may begin to question the value of investing in this technology. Moreover, the lack of transparency around AI adoption can lead to a lack of accountability, as companies may be hesitant to share their results with stakeholders. This can have significant consequences for businesses, as investors and customers may lose trust in companies that are unable to demonstrate the effectiveness of their AI strategies.
“Companies are struggling to measure the effectiveness of their AI strategies, with many relying on anecdotal evidence rather than hard data.”
What We Don't Know Yet
Despite the growing trend of AI adoption, there are still many unknowns when it comes to measuring the effectiveness of AI strategies. One of the biggest challenges is defining what constitutes success in AI adoption. Is it revenue growth, cost savings, or something else? Moreover, how do we measure the impact of AI on businesses, especially in industries where AI is still in its early stages? These questions remain unanswered, and it is essential that companies, investors, and policymakers work together to develop a framework for measuring AI effectiveness.
Key Takeaways
- Companies are struggling to prove the effectiveness of their AI strategies.
- Only 12% of companies have achieved significant benefits from their AI investments.
- The global AI market is expected to reach $190 billion by 2025.
- Companies are investing heavily in AI, hoping to gain a competitive edge.
- The lack of transparency around AI adoption can lead to a lack of accountability.
What to Watch
In the coming weeks and months, we can expect to see more companies sharing their AI adoption stories, both successes and failures. This will provide valuable insights into the effectiveness of AI strategies and help to build a more transparent and accountable industry. We will also see more investment in AI research and development, as companies seek to improve their AI capabilities and stay ahead of the competition. One key area to watch is the development of AI-specific metrics and benchmarks, which will help to provide a clearer picture of AI effectiveness and inform decision-making.
According to a report by McKinsey, AI has the potential to create up to $13 trillion in economic value by 2030.
The state of AI adoption in business is complex and multifaceted, with many unknowns and challenges. However, by working together and developing a framework for measuring AI effectiveness, we can build a more transparent and accountable industry, and unlock the full potential of AI. This requires a collaborative effort from companies, investors, and policymakers, and a willingness to learn from successes and failures.
