By Chris Brill, Field CTO, Myriad360

Experimenting with AI tools like ChatGPT or Copilot has become a natural starting point for many organizations. These off-the-shelf tools offer low barriers to entry and quick insights into AI’s potential. They allow teams to explore use cases, spark innovation, and begin building the foundational skills needed to work with AI.

However, the sandbox phase has limits. While it offers an opportunity to test AI’s possibilities, it isn’t designed for scaling innovation or aligning AI with business priorities. Organizations serious about leveraging AI need to move beyond experimentation and take ownership. This transformation isn’t just about infrastructure—it’s about embedding AI into the core of your business strategy and culture.

Step One: Taking Ownership of Your Technology

AI ownership begins with the right technological foundation. Organizations must move beyond generic tools to create scalable, reliable systems tailored to their unique needs. Achieving this requires investment in three critical areas:

The Infrastructure of Ownership

High-Performance Compute: Training and deploying AI at scale demands robust infrastructure. Enterprises often need GPU-powered data centers or scalable cloud solutions to meet these computational demands. Myriad360 specializes in designing and deploying high-performance systems, offering solutions that span GPU clusters, edge computing setups, and full-stack integration. With strategic partnerships, such as those with NVIDIA, Myriad ensures seamless deployment of AI-optimized systems.

Data Quality: AI is only as good as the data it relies on. Clean, structured, and regulation-compliant datasets are essential for meaningful results. Myriad helps organizations build robust data pipelines, addressing challenges like governance, accuracy, and compliance. Their consulting services focus on eliminating bottlenecks so businesses can focus on actionable insights.

Specialized Talent: Deploying AI successfully requires skilled engineers capable of tailoring solutions to unique business needs. Myriad bridges this gap by providing access to technical experts, including system architects and deployment specialists. In addition, their training and support services empower in-house teams to confidently manage and expand AI capabilities.

With these foundational elements, organizations can transition from experimenting with AI to embedding it as a core component of their operations.

Step Two: The Business Commitment

Owning AI doesn’t end with technology—it begins with aligning AI to business goals. Too often, organizations treat AI as a side project, failing to integrate it into their core strategy. Ownership requires deliberate commitment to using AI as a driver of measurable outcomes.

Aligning AI with Business Goals

Leadership must articulate a clear vision for how AI will create value, whether through optimizing operations, enhancing customer experiences, or driving innovation. Yet, many companies fall short: 76% of enterprises limit AI to just one to three use cases, missing opportunities for broader integration.

Access MIT’s Comprehensive AI Strategy Playbook

Breaking Down Silos

AI thrives when it’s embedded across an organization. Cross-functional collaboration ensures that AI initiatives address both technical and business needs. By fostering collaboration between engineers, business teams, and leadership, organizations can prevent siloed efforts that undermine AI’s potential.

Step Three: The Cultural Transformation

A critical, often overlooked component of AI ownership is fostering a culture of trust and adoption. Technology alone won’t create change—employees must believe in AI’s value and see it as a tool that empowers their work.

Fostering Confidence

Trust in AI systems requires transparency, reliability, and organizational alignment. Resistance to AI often stems from fear—fear of being replaced, fear of failure, or fear of the unknown. Organizations can address this by:

According to a Microsoft and LinkedIn report, while 75% of desk workers use AI tools, fewer than 40% have received formal training to do so effectively. This gap highlights the need for structured support to help employees fully embrace AI’s potential.

See Wired’s Insights on AI Adoption Challenges

Empowering Teams

A successful transformation requires buy-in from every level of the organization. Leadership must invest in creating a shared appetite for change, ensuring the financial, strategic, and cultural resources are in place to support adoption. Without this commitment, even the most advanced AI initiatives risk falling short of their potential.

The Rewards of Ownership

The benefits of AI ownership go far beyond immediate efficiency gains. By embedding AI into the core of your business, you unlock the ability to:

These rewards aren’t just theoretical—they’re achievable outcomes for organizations willing to make the commitment to AI ownership. With the right infrastructure, strategy, and culture, AI becomes more than a tool—it becomes a strategic asset that drives your business forward.