A Framework For Strategic Business Growth

Sr. Director of Product at Aisera, Jigar brings 15+ years in enterprise AI, GenAI innovation, agentic automation and product-led growth.

AI maturity isn’t about deploying AI tools or automating processes. It’s about aligning AI to your core business goals in a way that drives tangible value. However, many AI maturity models focus solely on an organization’s current state without offering a clear vision for advancing maturity.

Our organization’s AI maturity framework seeks to define AI maturity by using a more strategic perspective. This framework helps organizations determine where they currently stand while identifying the steps they need to take to align their use of AI with their business. From building foundational awareness to scaling AI across the business, this approach allows technical and business leaders to make informed, data-driven decisions that are more likely to lead to real business transformation instead of one-off projects and incremental gains.

Keep in mind that AI maturity is not a linear path. Organizations may start their journey at any stage, depending on their current capabilities, business priorities and strategic focus. Our AI maturity framework defines five strategic stages to help organizations understand where they are today and what steps to consider taking next.

Awareness: Setting The Stage For Strategic AI Adoption

Organizations with little to no AI experience must first develop a strategic understanding of AI’s potential across the organization.

Organizations at this stage should focus on analyzing industry trends and use cases, benchmarking against competitors and identifying 3-5 potential areas where AI could deliver tangible business value. This phase may also include training programs for key stakeholders, forming a center of excellence and ensuring that core infrastructure like data pipelines and governance frameworks are prepared to support future AI development.

KPIs to advance to the next stage:

• >80% basic infrastructure readiness

• Industry analysis completed

• Initial use cases identified

Exploration: Testing The Waters With Low-Risk Pilots

Organizations with the groundwork in place can explore AI’s potential through small-scale pilots and proofs of concept (POCs). With these projects, organizations can explore their AI options and start to identify gaps they may need to fill before advancing with more ambitious initiatives. One gap they may need to fill is the technical capabilities of their team, which could require training, hiring or strategic acquisitions.

KPIs to advance to the next stage:

• 2-3 POCs initiated

• >50% POC success rate

• ROI metrics for the POCs defined

• Resource gaps identified

Adoption: Operationalizing AI In Core Business Areas

In this stage, organizations are ready to make AI part of their daily life in specific domains like IT service management or customer support. Once the use case is fully operationalized, the organization can use its learnings to draft the enterprise standards it will need to roll out AI across the organization.

The emphasis here is to build repeatable processes, standardize development and deployment practices, implement MLOps pipelines and establish governance frameworks to manage risk, privacy and performance. To secure user engagement, organizations should build onboarding frameworks and change management strategies while monitoring the impact that AI has on both productivity and the employee experience.

KPIs to advance to the next stage:

• >70% resolution rate for the deployed use case

• A governance playbook created to onboard new use cases and domains

• Technical staff resource gaps filled

• Targeted % rate for user adoption achieved

Expansion: Leveraging Cross-Functional AI

At this stage, organizations have mastered the use of AI in one or more domains and are now using a platform approach to leverage AI across functions. Organizations in this stage typically approach new initiatives with an AI-first mindset, which in turn influences strategic planning, budget allocation and product development.

Scaling AI across the enterprise isn’t just about extending capabilities to more departments, but creating a connected, closed-loop AI ecosystem that continuously learns, adapts and improves. With each interaction, the platform optimizes itself, identifying patterns, refining ontologies and implementing proactive measures that can deflect even more incidents before they reach human agents. This approach streamlines processes while fostering cross-functional alignment to ensure that AI initiatives in one department inform and enhance strategies in others.

KPIs to advance to the next stage:

• >50% of decisions are made by AI

• Achieved desired employee satisfaction with AI tools

• # of AI initiatives that are live in production

• ROI that consistently exceeds expectations

Transformation: Redefining Business Models Through AI

At the highest stage of AI maturity, organizations have fundamentally transformed how they operate, compete and serve customers and employees by leveraging AI as a strategic driver for reshaping their business model.

Organizations in this stage have deeply embedded AI in every department and at every layer of the organization. AI is used to develop new products, anticipate market shifts, optimize resource allocation and allow the organization to quickly adapt to changing conditions and new opportunities.

KPIs to maintain momentum in this stage:

• 75% of processes are fully automated

• 80% of strategic decisions are informed by AI

• 1-3 new AI-driven products or services launched

• Industry recognition for AI excellence achieved

From Exploring Capabilities To Building A Competitive Edge

Every business wants to realize the promise of AI, but few take the time to understand the context of their own organization.

The value of a maturity model lies in knowing where you stand while helping you identify how to iterate and move forward. By leveraging a strategic, multidimensional framework, organizations can shift from scattered, one-off AI projects to focused, high-impact initiatives that drive measurable outcomes and lasting strategic value.

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