Artificial Intelligence continues to reshape how organizations deliver value, manage risk, and improve performance. At the 2026 CMMI Capability Creates Conference, Cara Norris and Felicia Reed had the opportunity to explore one of the most important developments in this space: the new CMMI Artificial Intelligence Maturity (AIM) framework with 20 Practice Areas, a structured model for helping organizations assess, govern, improve, and measure the maturity of their AI capabilities. Their participation provided valuable insight into how Analytica can continue building on its strong process foundation while preparing for the next generation of AI governance, maturity, and responsible innovation.

Why AI Maturity (AIM) Matters

AIM helps organizations move beyond isolated AI experimentation and toward mature, governed, measurable, and repeatable AI capabilities. Successful adoption is not just about technology. It also depends on the strength of the processes, governance structures, risk controls, performance measures, and organizational culture that support AI use.

Learning from Early AIM Pilot Participants

One of the most valuable parts of the conference was hearing lessons learned from early AIM pilot participants, including KPMG and IBM. These organizations demonstrated how AI maturity principles can be applied in real-world environments to improve stakeholder alignment, define AI scope, establish objective evidence, manage AI-related risks, and create meaningful improvement roadmaps.

According to the CMMI Appraisal team, IBM’s key AI-enabled workflow transformation provided $4.5B in production savings exceeding their $2B goal. Approximately,10M hours of work were automated, their customer net promoter score increased by 15 points and employee engagement scores also increased by 20 points. The area of focus included Sales and Customer Support (i.e. digital self-service, modernized contract center, agent assistance, contract center insights), Modernizing Finance (i.e. pricing approval workflows, contract intelligence, streamlining orders & billing), Procurement Supply Chain (i.e. procure to pay, supplier management, contracts and purchase order management, inventory management) and Augmented HR Support (talent recruitment, onboarding, payroll and compensation, employee support). Source:  IBM CMMI AIM Pilot Experiences and Lessons Learned Presentation.

Strengthening AI Risk Management and Organizational Resilience

A recurring theme throughout the conference was the importance of using AIM to strengthen risk management and organizational resilience. Many organizations are investing heavily in AI while still working through governance gaps, inconsistent implementation, unclear accountability, data quality concerns, security risks, regulatory exposure, ethical considerations, and challenges demonstrating business value.

AIM helps address these challenges by giving organizations a structured way to assess AI maturity, identify governance and performance gaps, manage AI risk, and integrate AI into existing business operations. This creates a path from fragmented experimentation to a disciplined, scalable approach that improves transparency, trust, accountability, and measurable outcomes.

Why Analytica Is Well Positioned

The conference confirmed that Analytica is exceptionally well positioned to incorporate AIM practices and AI governance requirements into the existing A2O framework and integrated management system. Analytica already has a strong foundation in CMMI, ISO 9001, ISO 27001, ISO 20000, cybersecurity, risk management, quality assurance, training, auditing, and performance measurement. These established capabilities directly support many of the governance components emphasized throughout AIM.

Rather than requiring a standalone effort, AIM is designed to integrate with existing management systems. By leveraging A2O processes, quality governance, audit practices, and a culture of continuous improvement, Analytica can efficiently build AI governance into the way work is already planned, performed, measured, and improved.

Key Takeaways for Analytica

• AIM provides a practical model for governing AI responsibly and measuring maturity over time.
• AI success depends on more than tools; it requires clear processes, accountability, controls, and performance measures.
• Early pilot participants, including KPMG and IBM, demonstrated the value of applying AIM in real operational environments.
• Analytica’s A2O framework provides a strong foundation for integrating AIM practices without creating unnecessary duplication.
• Responsible AI governance can help reduce risk, improve transparency, and demonstrate measurable business value.

A CMMI Artificial Intelligence Maturity appraisal can demonstrate that Analytica has mature, responsible, and repeatable AI practices that enhance the quality, security, and reliability of AI solutions. It strengthens customer confidence, provides an avenue for providing customer innovations, differentiates the company in the federal marketplace, further reduces our risks through effective AI governance, and supports continuous improvement, positioning Analytica to deliver trusted, mission-focused AI capabilities with confidence.

Looking Ahead

As AI continues to evolve, Analytica has an opportunity to lead with intention by applying proven process improvement principles to emerging AI capabilities. The insights Cara Norris and Felicia Reed gained at the 2026 CMMI Capability Creates Conference reinforce the value of building AI governance into our existing management system, aligning innovation with risk management, and ensuring AI adoption remains responsible, measurable, and mission-focused.

 

About Analytica 
Analytica is a data and analytics consulting firm helping federal government agencies accelerate mission impact through data modernization, AI readiness, and product-driven approaches to data asset management.