AI Deployment
Summit

Enterprise Strategies for AI Success

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February 6,
2025

Virtual Summit

Artificial intelligence (AI) is often likened to the beginning of the Internet—an era brimming with transformative potential and exciting possibilities. And with good reason.

Business leaders are optimistic that AI will continue to unlock new innovations that deliver meaningful value for organizations and society at large.

Enthusiasm for AI among IT professionals also remains high. A recent McKinsey survey found that 65% of organizations are now regularly deploying generative AI across various business functions, underscoring its rapid integration and the enthusiasm surrounding its possibilities.

Even in these early stages, AI adoption is already making a measurable mark; among companies that have adopted AI/ML technologies, Forrester found that 74% have reported a positive impact.

All this said, at the start of 2025, AI advancements still face challenges. Notable among them:  

• A lack of trust
• lack of skills
• challenges with effective data governance
• lingering uncertainty over how best to realize tangible returns on AI technology investments.

Enter Agentic AI – A Step Beyond

Enter agentic AI. A step beyond the conventional request-and-response implementation of generative models, this emerging technology introduces "agents" which differ from traditional chatbots in two principal ways. 

• First, agents are capable of performing meaningful tasks by reasoning through user inputs often in a chain-of-thought process, much like a human. 
• Second, agents have “agency” – the ability to autonomously devise and execute strategies, while accessing tools required to achieve results.

 Let’s explore the potential of agentic AI and the data-driven advancements poised to define its important role in the enterprise.

Foundation First, Building from the Base Up

Preparing for an AI-driven future starts with a dual focus: building a strong data foundation and strategically identifying the right business use cases for AI. The opportunities for leveraging AI are broad, spanning business intelligence, fraud prevention, customer relationship management, and content creation. However, none of these applications can succeed without reliable data as their backbone.

Businesses can build a strong foundation for AI’s full potential by emphasizing data integrity, governance, and innovation. Regardless of how AI evolves, its effectiveness will always depend on the quality and integrity of the data it relies upon.

Establishing this foundation requires focusing on six essential attributes:

Diversity
Timeliness
Accuracy
Security
Discoverability, and
Accessibility

This above checklist provides a practical guide for ensuring that data is prepared to fuel AI reliably. With each foundational pillar, organizations can pave the way for sustainable growth in an AI-powered future.  

Agentic AI – A Journey Not Only a Destination

All this said, the steps each company takes to achieve these qualities will vary -- depending on an organization’s data maturity. This means building a data foundation will be a journey, not a destination. Further, organizations must also prioritize strong governance and foster a culture of innovation to successfully integrate AI initiatives. Though challenging, these efforts are essential to advancing AI projects, cultivating new capabilities, and ensuring safety and trust throughout implementation.

The driving concept behind agentic AI’s next generation thinking is to evolve AI beyond a mere tool into a dynamic and autonomous force. It redefines how large language models (LLMs) are utilized.

In fact, Forrester’s Top 10 Emerging Technologies for 2024 identified “agentic AI” as the most transformative innovation on the horizon. Its promise lies in delivering more sophisticated and resilient automation capabilities while driving advancements in other emerging technologies.

Done correctly, organizations will move beyond their current “request-and-response” frameworks to more operational, decision-making roles.

And best of all, agentic AI is ready to deliver the tangible benefits sought after by so many organizations.  AI agents can harness advanced language models to perform complex tasks, make autonomous decisions, and interact on behalf of organizations or individuals. This potential becomes even more compelling when multiple agents collaborate, creating a digital ecosystem that can drive value-rich outcomes—an early vision of a digital factory of the future.

In summary, agentic frameworks are poised to elevate AI to address more complex and consequential use cases, the exact type of challenges organizations struggles with every day.

A Brighter (and Flexible) Future with AI Agents 

In the world of agentic AI, the future of AI extends well beyond the current buzz around generative models.

That said, delivering the benefits of agentic AI will require organizations to proactively build a foundation capable of supporting all forms of AI—both those in existence and those yet to come. But those organizations that thrive in this evolving AI landscape will succeed by building a strong data foundation, ensuring governance for responsible use, and fostering a culture of innovation.

By investing in these pillars, organizations can unlock AI’s transformative potential, driving innovation, creating value, and securing their place in the AI-powered future.

Nick Magnuson, as Head of AI at Qlik, is aa experienced leader in applying AI/machine learning to solve real-world business problems. He focuses on way to leverage modern AI, AI agents, predictive analytics, ML and myriad data sources and integration to address key business problems and goals across all industries.