The AI landscape has undergone a significant shift over the past 18-24 months, moving from initial experimentation to growing confidence and a focus on business transformation. 

This evolution is clearly reflected in the busy World AI Summit in Amsterdam, which Alan Flower, EVP and Global Head of Cloud and AI Labs at HCLTech, says “really reflects some of the trends around adoption that we're seeing in the industry.”

Just 18 months ago, he suggests that many of the world’s largest organizations were unsure whether AI, and its subset generative AI (GenAI) specifically, would truly deliver business value. However, the tide has turned, with organizations now seeing tangible results from early AI deployments, particularly in domains like software engineering. 

As Flower notes, “our clients have collected a lot of positive metrics around the productivity gain from AI.” 

This growing confidence has now extended beyond the technical realm into the business domain. Senior leaders across industries are becoming “utterly convinced that GenAI is going to bring real value to their organization,” according to Flower. 

The focus has shifted to “value stream innovation” and “value stream transformation” — using AI to drive meaningful business transformation. 

The rise of industry-specific AI

Accompanying this shift in mindset is a move away from generic, horizontal AI experimentation toward more targeted, vertical solutions tailored to specific industry needs. 

Flower observes that the demand coming into HCLTech's AI Labs is “utterly dominated by clients who have found a value stream within a specific business domain where they see a need for a vertical solution.” Clients across sectors, from healthcare and manufacturing to oil and gas, are identifying unique use cases and processes where they believe generative AI can add significant value.

This industry-specific approach, reflecting the growing trend in cloud computing, is replacing the more generic chatbot and contact center solutions that were prevalent in the past. 

The role of multicloud and hybrid cloud 

As AI deployments move from experimentation to production, the importance of hybrid and multicloud strategies has become increasingly clear. While clients may start their AI journey with a single hyperscaler, the pragmatic reality is that, as Flower states, “AI, just like cloud is a hybrid, multicloud journey.” 

Concerns around data regulation, accessibility and exposure are driving organizations to adopt more diverse cloud architectures. 

HCLTech’s recent Cloud Evolution: Mandate to Modernize research report cited by Flower provides the “proof point” that multicloud and hybrid cloud are essential for successful AI and GenAI deployments. 

AI expectations for the next 12 months 

Looking ahead, Flower predicts that the next 12 months will see the emergence of even more advanced AI capabilities. Beyond conversational AI, organizations are now moving toward “agentic systems” — AI that can make decisions and take responsibility for outcomes. Multimodal AI, including speech, is also expected to be the next big inflection point. 

Additionally, the rise of specialized AI models that complement large language models (LLMs) will become the norm, as organizations seek to create more accurate and tailored solutions for their end users. 

The combination of agentic systems, multimodal solutions and multimodal architectures is, “poised to transform the AI landscape in the near future,” adds Flower.