Organizations will take the next decisive steps as AI delivers genuine bottom-line impact
There is a bright future ahead for AI, but we’re not quite there yet. It's now been more than two years since the launch of ChatGPT. Since then, organizations have been experimenting with generative AI, but we haven't yet seen many pilot projects evolve into truly transformative processes and business applications. This situation will change in 2025.
While AI’s potential is clear, the hype is deafening. So far, the technology hasn’t lived up to its promise. Just 20% of businesses reported earnings benefits from generative AI over the past year. Adoption has been cautious, focusing on low-effort applications like chatbots that generate tailored answers from manuals and documentation. While these solutions enhance customer experiences—such as providing precise troubleshooting steps for a specific TV model—they fall short of being transformative, requiring no significant changes to a company’s data or AI strategies. The principle of “garbage in, garbage out” still applies. However, there is reason for optimism: many organisations are now investing in foundational capabilities that could unlock hyper-personalised experiences and drive greater value by 2025.
To understand what’s ahead, we just need to look at the vast range of use cases that showcase AI’s benefits. Life sciences is an area that will lead AI advancements, with areas such as drug and vaccine development accelerating rapidly, as enhanced data processes speed up innovation and make it faster and easier to make treatment breakthroughs. Across the wider healthcare sector, emotional AI has the potential to improve mental health diagnosis by drawing on unstructured data analysis to deliver genuine benefits for citizens and employees. In manufacturing, the automation of supply chains not only drives up efficiency but also alleviates geopolitical and environmental pressures.
Financial services are also being reshaped. Hedge funds are using generative AI to outperform human analysts in stock price prediction while significantly reducing costs. Compliance functions are evolving, with AI automating data management and simplifying regulatory submissions, ensuring firms can meet growing regulatory requirements without stifling growth. Self-service, powered by AI, is now a critical customer touchpoint across all sectors, with half of businesses adopting AI-driven helpdesks. As this trend matures, self-service solutions are poised to become a cross-sector standard. across all sectors, with half of businesses adopting AI-driven helpdesks. As this trend matures, self-service solutions are poised to become a cross-sector standard.
The opportunities are significant. However, there is no hiding from the fact that the challenges are also substantial - although they are certainly smaller and more surmountable than they were two years ago. As adoption escalates, it is critical to balance efficiency with customer experience in a measured, thoughtful and analytical manner. Take, for example, agentic AI. Although it is becoming an increasingly convincing analog for human interaction, it will not and may never eliminate the need to employ humans to deal with customers. Consumers and business customers are not about to lose their desire for the human touch that technology simply cannot deliver right now.
As we move forward into an AI-enabled future, a strategy all organizations should be sure to enact is streamlining access to data and ensuring it is accurate, integrated, up-to-date and well-governed. Delivering AI transformation involves much more than simply buying a GPU and training a large language model. If the data is not ready for AI, neither is the organization that owns that data.
The old adage of “garbage in, garbage out” is still true today and will remain so for the foreseeable future. Data fuels AI. If that fuel is outdated, inaccurate or incomplete, the model is working at a major disadvantage and will generate outputs that are neither useful nor accurate. To make the most of AI, companies require a unified view of their data to improve customer engagement. This requires complex matching, which AI can enable through metadata management, automated integration and single views.
There will be a shift towards AI data management throughout 2025, making data available to non-technical users and ensuring they adhere to regulations such as the GDPR. Compliance will become ambient - baked into processes automatically so that individual staff members can adhere to regulations effortlessly. In data governance, AI facilitates controlled access, protects privacy, and streamlines documentation, driving a shift toward AI-ready data management in 2025.
Until now, businesses have been waiting until the technology matures to truly transform data operations. Now, we will see the situation turn around as AI delivers genuine bottom-line impact. There’s a bright future ahead, and 2025 will be the year organizations take the next decisive steps on their AI journeys.
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