Unlock Enterprise Growth with AI Center of Excellence

Why an AI Center of Excellence Is the Key to Enterprise Transformation

AI is often considered a magical must-have tool, the mere possession of which is believed to transform businesses. But is it truly the case? Well, not entirely untrue! A recent BCG survey, ‘Where’s the Value in AI?’, observed that 4% of companies have unlocked substantial returns from advanced AI capabilities, while 22% are beginning to see gains. But the same report also reveals a different side of the story. A whopping 74% are still struggling to translate their AI investments into tangible value¹ as they are stuck in the pilot mode. Many roadblocks hinder their journey from isolated pilots to enterprise-wide deployments. Here are what’s holding them back:

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This is where an AI Center of Excellence (COE) becomes a game-changer. It provides the backbone to ensure each AI investment drives measurable business outcomes and avoids common pitfalls. By centralizing expertise, standardizing best practices, and fostering innovation, a COE ensures each AI investment delivers measurable outcomes and sidesteps common pitfalls. It turns data and AI into actionable insights, automated efficiency, and a sustainable competitive differentiator.

At TechM Consulting, we help clients scale AI @ Speed by designing, launching, executing, and monitoring their AI COE to co-create lasting value.

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Strategy Alignment and Oversight

The COE begins by aligning the organization's AI initiatives with an overarching strategy, vision, and growth goals, whether that involves expanding into new markets, diversifying the product portfolio, or enhancing customer engagement.

To establish solid governance, the COE will:

  • Identify and onboard executive sponsors and form a cross‑functional steering committee (data, infrastructure, security, legal, business, etc.)
  • Define and finalize roles and responsibilities within the operating model, which can be democratic, hub‑spoke, or hybrid/federated, based on the organization’s current structure and AI maturity
  • Employ a diverse mix of people and skills, from engineers and architects to quality assurance and security experts
  • Establish an innovation incubator to capture and test new ideas

Once set up, the COE acts as the gatekeeper for all AI use cases. Every proposal is evaluated on a single yardstick (ROI, technical fit, strategic alignment, etc). They also oversee risk management, including regulatory compliance across all relevant authorities.

Discovery and Roadmapping

The COE leverages Tech Mahindra’s proprietary Pathfinder and Discover workshop, which is built on design‑thinking principles, to uncover organizational friction points and identify scalable Minimal Viable Product (MVP) use cases. For each use case, the COE then:

  • Evaluates ROI: Analyzes costs, risks, and expected benefits
  • Prioritizes Efforts: Ranks use cases by overall value and complexity
  • Creates a Roadmap: Develops a structured, domain‑specific plan for implementation

While these initiatives are being carried out, three strategic pillars—AI capabilities, data readiness, and technology standards— will operate concurrently to ensure these initiatives scale smoothly and sustainably.

1. AI Capabilities: The people and culture foundation is built to drive adoption through:

  • Review and reimagination of workflows with AI-led process mining
  • Implementing actions to promote cultural transformation
  • Conducting a skill gap analysis, followed by data and AI upskilling to boost organizational literacy
  • Driving ‘Citizen-led-Innovation,’ to guide ideas from the grassroots level within the organization

 2. Data Readiness and Governance: The data ecosystem for high‑velocity AI is created by:

  • Ensuring access to all internal data sources or acquiring external data as needed
  • Enriching data using internal or external sources to deepen insights for successful AI implementation
  • Deploying Data Lakehouse or Data Mesh architectures to handle and store large amounts of data effectively
  • Implementing data versioning and maintaining audit trails and lineage across organizational data for compliance

3. Technology and Standards: The technological infrastructure is put in place by:

  • Applying Build vs Buy vs Blend decisions based on urgency, customization needs, and ecosystem compatibility
  • Establishing continuous AI and data verification and validation pipelines to detect and correct model drift, bias, or hallucinations
  • Implementing unified policies and standard operating processes for AI development, deployment, and maintenance
  • Simplifying collaboration methods with partners, vendors, and alliances for speed and consistency
  • Overseeing the development of platforms, libraries, and infrastructure for the success of the entire AI program

Responsible AI and Business Impact

As the COE advances its three pillars, ethics and risk management form the cornerstone for ‘Responsible AI’ development and deployment. As mentioned earlier, it ensures effective risk management, including legal and regulatory compliance across every data and AI initiative. To monetize these efforts, they track ROI and quantify business impact, then use those insights to craft a two‑year investment roadmap that drives scalable AI across the organization.

Conclusion

An AI Center of Excellence transforms isolated pilots into an enterprise-wide AI capability by aligning initiatives with strategic goals and governance, establishing robust data and technology foundations, and fostering the right skills and culture. 

Tech Mahindra’s Data and AI Consulting team makes this a reality by applying a structured framework that involves readiness assessments, use-case discovery, technology and data architecture alignment, proof of value, and a tailored transformation roadmap to turn insights into impact. Supported by deep domain expertise, proven methodologies, and hands-on change management, we guide you through governance design, architecture development, and ongoing value realization to achieve sustained growth and a competitive advantage.

Chart your AI COE journey with Tech Mahindra. Talk to our experts in Data & AI Consulting.

About the Author
Aditya-Shiralkar
Aditya Shiralkar
Head, AI & Data, TechM Consulting, Tech Mahindra

Aditya brings over 25 years of experience in customer-facing roles, leading digital consulting and initiatives that specialize in cloud-native AI-ML services and products to address industry challenges. He oversees the AI & Data Consulting team, emphasizing collaboration and ensuring high-quality results. Aditya is passionate about equipping clients with strategic insights, actionable recommendations, and scalable solutions that drive results.