The era of agentic AI is here, and enterprises can no longer afford to view AI as an optional enhancement. The projected rise in AI investment from 19% to 31% over the next two years (see Exhibit 1) underscores a broader industry shift toward data-driven and AI-centric transformations. This trend of AI leading the technology investment rush surfaced in HFS Research’s recently published AADA Quadfecta Services Horizons study. The baton of being the most vital enterprise technology area is now passed onto AI. What AI can do to reimagine the “ways of working” is unprecedented and will catapult the industry to a whole new direction.
A 63% increase in AI spending reflects enterprises’ strategic shift, treating AI as essential for driving innovation, agility, and scalable value. Many technologies in the past have promised and, to a certain extent, delivered these benefits, but their scope and magnitude of impact have been limited. Moreover, these technologies have mostly optimized the existing process rather than reimagining it. For example, traditionally, analytics helped contact center agents identify call patterns, suggest responses, understand permutations, and communicate efficiently, leading to gains such as reduced handling times and better call resolution.
With agentic AI coming into the fray, the rules of agent-customer interaction are likely to change:
Agentic AI is reshaping the enterprise landscape, delivering smarter, hyper-efficient, and highly personalized solutions that drive unprecedented innovation and business value. Even non-digital industries are leveraging AI for new revenue streams and operational efficiencies. This aligns with the Agentic AI HFS 2030 Services & Technology Vision, highlighting the convergence of AI, data, and automation for greater agility and innovation. The trend toward agentification—where AI augments human roles—is fueling investment, blending human expertise with AI-driven intelligence. AI is becoming the cornerstone of modern, data-driven enterprises—essential for future success.
As AI reshapes business landscapes, enterprise leaders cannot afford complacency. Integrating AI seamlessly into existing workflows is a significant challenge. The lack of a robust AI governance framework could expose businesses to security threats and AI bias, jeopardizing their strategic objectives. Enterprise leaders must overcome technical obstacles and address skill shortages and ethical concerns. Prioritize AI investments that align with strategic goals, establish strong data governance practices, and be ready to pivot as AI regulations evolve. Start today or risk falling behind.
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