Sumit Anand, CIO and EVP at Academy Sports + Outdoors, explains how a cross-functional AI council, agent-based tools, and a disciplined approach to data architecture help the$6 billion retailer create value every quarter, and why CIOs who wait for a dedicated AI budget are missing the point.
How is AI impacting growth and transformation strategy at Academy Sports + Outdoors?
We see AI as more than just a technology trend. It’s becoming an important capability reshaping how we grow, operate, and serve our customers. It’s also increasingly becoming part of how we think about the future of the business.
Our philosophy is straightforward: innovation only matters if it creates real value, and we’re applying AI where it can improve the customer experience, accelerate decision-making, and help the business move faster and more effectively.
What makes this moment different is that AI is changing the traditional transformation playbook. Historically, companies often focused on modernization first and innovation second. We don’t think that approach works anymore. The pace of change requires organizations to modernize and innovate at the same time. That’s the path we’re pursuing — building for the future while continuing to create value today.
What are some examples of this strategy in action?
On the customer side, AI helps us create a more intuitive and personalized digital experience. We enhanced our website search capabilities to improve product discovery, and this year we launched our AI agent-based search assistant Scout to make shopping more conversational and contextual. Instead of simply searching for products, customers can describe what they’re trying to do — like preparing for a camping weekend — and receive recommendations tailored to that experience. That’s important because it helps us move beyond transactions and become more of a trusted guide for our customers.
Inside the organization, AI is also changing how we work. By deploying more than 1,000 Copilot licenses, we’re giving team members tools that reduce repetitive work, improve productivity, and create more time for strategic thinking. It’s about increasing the capacity of the organization and allowing people to focus on higher-value work.
Ultimately, we see AI as a way to amplify human potential, both for our customers and teams. The opportunity isn’t just automation, but building a more intelligent, responsive, and adaptable enterprise. The companies that will lead in this next era are the ones that combine innovation with business discipline, and that’s how we’re approaching AI.
How are you executing on these goals?
Execution starts with a broader strategy we call data as a product. It’s about treating data as an enterprise asset that can create repeatable value across the business, rather than a byproduct of systems or processes.
Early on, we faced a choice to either follow a more traditional implementation model and wait years for insight, or focus on creating value incrementally while building the long-term foundation for scale. We chose the latter. In an environment with petabytes of information and hundreds of integrated elements, speed to value matters.
That’s why we established a cross-functional AI council led by IT and made up of leaders from 12 business functions. Its role helps activate the business by identifying high-value use cases and moving them forward with speed and accountability.
What makes the model work is leadership alignment. Our senior leadership understands that tech isn’t separate from business strategy. It’s one of the key levers to drive growth, improve EBITDA, strengthen the customer experience, and create long-term shareholder value. When that alignment exists, decisions move faster and we improve adoption.
How are you approaching the governance and ethical considerations of AI?
We take governance and data security extremely seriously because trust is foundational to scaling AI responsibly. Our use of Copilot operates within a private cloud environment, which helps keep our data secure within our network, and supports broader adoption across the organization.
We’re also investing in the capabilities needed to govern AI at scale. Working with a consulting partner, we help teams build a well-governed agent factory model and teaching them to build agents, as well as secure, manage, monitor, and scale them responsibly.
Education is another important part of the equation. We’re expanding AI learning across the enterprise, including targeted training for functions where adoption requires especially thoughtful judgment and oversight.
We don’t view innovation and governance as separate tracks. If governance moves too slowly, risk increases. If innovation moves without governance, trust breaks down. The goal is to put the right guardrails in place so the business can move with speed and confidence.
How is the role of the CIO changing during this AI era?
The CIO role has fundamentally changed. The days when CIOs could focus on a handful of large tech programs over multi-year timelines are over. Today, the role sits at the intersection of strategy, innovation, execution, risk, and talent.
In the AI era, CIOs have to remove friction from technology deployment, help upskill teams, and enable business functions to adopt emerging technologies in ways that are practical, secure, and aligned with enterprise priorities. The role is no longer just about delivering systems but creating the conditions for innovation to scale responsibly across the business.
AI is also changing how decisions get made within technology organizations. We’re seeing more distributed ownership, with leaders across the company helping shape AI investment decisions. That’s a positive shift because some of the best use cases come from the people closest to the operational challenge or customer need.
How are you thinking about your role as architect of your company’s future, from a systems perspective?
One of the first things I did after joining Academy was establish a dedicated enterprise architecture leadership role because in an AI-driven environment, architecture is a strategic business capability, not just a technology discipline.
When you think in enterprise systems, you stop viewing platforms, data, and processes as isolated components. You start seeing how interconnected they are and how they shape the speed, intelligence, and adaptability of the business. The architecture decisions we make today will influence how effectively we can grow and innovate over the next decade.
Our roadmap reflects that thinking. We’re modernizing the core, advancing ERP transformation, integrating backend systems, building a semantic layer, and evaluating platforms that can unlock meaningful use cases in the near term. But the broader objective is bigger than any one initiative. It’s about creating an enterprise where systems work together seamlessly, and innovation can scale more effectively.
From that perspective, my role is to oversee technology decisions as well as help build a connected and adaptable enterprise that can turn emerging technology into long-term business advantages.
What you’re doing from an architectural standpoint and beyond is making bets on a future that doesn’t exist yet. What’s your advice for a CIO stepping into their first role?
Don’t wait for perfect conditions. If you’re waiting for a dedicated AI budget before taking action, you’re already behind.
Stepping into a CIO role today means recognizing you’re helping shape the future operating model of the business, not just inheriting a technology agenda. That requires making thoughtful bets before every answer is fully known. It means understanding where the organization is ready to move, where trust still needs to be built, and where the foundation needs strengthening.
You don’t need to start with a massive transformation program, but you do need to start. Build proof points, establish trust by pairing ambition with discipline, put the right guardrails in place so innovation can move responsibly, and most importantly, create momentum.
Read More from This Article: At Academy Sports + Outdoors, AI is a team effort
Source: News