Editor’s note: Professional services company Cognizant recently published a paper detailing how it is harnessing GenAI to strengthen the deployment of CMMI by infusing GenAI capability across the various CMMI practices that underpin the software and services lifecycle. Below, ISACA Now visits with the Cognizant team for a Q&A interview to explore the connection points between AI and CMMI adoption, and the results that Cognizant has experienced. Prabha Anand, Vice President, Delivery Excellence, Cognizant, spoke to us and shared her insights.
ISACA Now: Please provide a brief overview of Cognizant's history with CMMI and how the adoption has evolved over the years.
Cognizant is one of the world's leading professional services companies, transforming clients' businesses and operating and technology models for the digital era. Our unique industry-based, consultative approach helps clients envision, build and run more innovative and efficient businesses. Headquartered in the US, Cognizant was ranked 213 on the Fortune 500 in 2024 and is consistently listed among the world’s best companies.
Cognizant's impressive growth journey to be a Fortune 500 company and a global leader in information technology has been based on a solid foundation of robust technology, innovation and excellence in delivery for the past 30 years.
We embarked on the journey of CMM by being assessed at CMM Level 4 in 1998 within four years of our inception. We showcased our capability to continuously innovate and improve by moving to CMM Level 5 in December 2000.
Cognizant quickly adopted the new CMMI model with the assessment at Maturity Level 5 in 2003 and has continued to maintain it as the model has evolved over time.
Cognizant is currently assessed at CMMI 2.0 Maturity level 5. Cognizant has initiated work on getting itself certified on CMMI 3.0 for Development and Services domain capabilities by November 2025. The scope of the CMMI appraisal includes all services delivered by Cognizant across global locations.
ISACA Now: According to ISACA AI research from this year, the majority of organizations do not have AI policies in place. What do you see as some of the most important steps that organizations should take to make sure AI is implemented responsibly and with sound governance?
Unlike the software solutions of the pre-generative AI world, generative solutions cannot be built, tested, and released into an ecosystem without continuous oversight—embedded in the culture. With all of the compelling use cases for generative AI and the immediate accessibility of public tools in the market today, it can be easy to get carried away in the AI hype. That same consumer availability of basic AI tooling can trivialize the complexity and downplay the policy, process, partnership and skill required to build tailored, production-grade solutions. It all starts with setting strong, enforceable principles for responsible AI development.
Cognizant also recognizes that the development and usage of AI systems should be responsible and ethical. Hence, as part of the strategic plan drawn out to harness the power of AI, we set up a specific working group to draw up the responsible AI framework and design platforms to govern the development and usage of AI.
One of the critical tasks entrusted to the responsible AI (RAI) working group is to define, roll out and evangelize Cognizant's responsible AI policy and principles across the organization, including to company associates and vendor partners. The Delivery Excellence team collaborated with RAI working group to roll out extensive and detailed delivery methods, metrics and guidelines to enable the delivery teams to adopt responsible AI practices effectively, supported by mandatory and need-based training programs.
At Cognizant, we are helping to build responsible, enterprise-scale AI in hundreds of organizations and within the core of our own business. Based on this experience, we believe enterprises need to act now in five areas:
- Align leadership to a consistent vision and accountabilities. AI is a CEO issue that requires collaboration across all functions of the organization. Leadership teams should spend time discussing the issues surrounding responsible AI and should agree on areas of opportunity, approaches to governance, responses to threats and accountabilities for actions.
- Manage standards and risks. Establish a governance, risk and compliance framework to standardize good practices and systematically monitor AI-related activity. Considering the full scope of an AI-powered system within this framework, including training data, AI models, application use cases, people impact, and security, is critical.
- Create a focal point of expertise. Responsible AI cannot be managed without centralized transparency and oversight of activity. Creating a center of excellence for AI enables scarce expertise to be leveraged most effectively and provides a coherent view to leadership, regulators, partners, development teams and employees.
- Build capability and awareness. Sustaining responsible AI practices requires everyone in the enterprise to understand the technology's capabilities, limitations and risks. All employees should be educated on the concept of responsible AI, the vision and the organization's governance processes. Select groups will then require further assistance through training and coaching to take a more hands-on role in developing and leveraging AI solutions.
- Codify good practice into platforms. AI is a pervasive, horizontal technology that will impact almost every job role. If we want teams to build trustworthy solutions quickly, they will need the data and tools for the job. Platforms for AI can make sharable assets accessible for re-use, ensure that effective risk management is in place and provide transparency to all stakeholders.
With these five elements in place, organizations are set up to operationalize their position on responsible AI, enabling the enterprise to execute and govern activities effectively. We consider this an urgent priority for every organization adopting AI or exposed to AI-powered threats.
ISACA Now: Cognizant recently released a white paper on integrating generative AI into CMMI: how has integrating AI with CMMI improved Cognizant's performance?
Cognizant has developed a structured plan to infuse GenAI systems in two phases to aid the organization and implement the CMMI best practices effectively and efficiently across all the capability areas.
Phase I of implementation has focused on:
- Promoting Innovation across the organization: The GenAI solution, Cognizant Bluebolt assistant, has improved the quality of idea generation and resulted in improving the quality of ideas adopted by projects. This has led to a productivity improvement of >15% across the projects implementing the ideas.
- Industrializing the methods across all projects: Cognizant Process Assistant and Cognizant Knowledge Assistant has helped recommend the right process steps, guidelines, templates, metrics, benchmarks and learnings from past projects. These solutions have helped the organization improve the quality of delivery and reduce the evangelization and deployment time by approximately 50%.
- Extracting obligations and commitments made to the client: With the Cognizant Obligation Extractor, Cognizant has reduced the time associates spend going through the Master Service Agreement (MSA) and Statement of Work (SoW) by more than 20%.
- Effective planning and tracking of independent assessments: The Cognizant Virtual Assessment Assistant has significantly reduced the time spent by Assessors in gathering information about a project, doing the preliminary assessment of a project, drawing up focus areas for the assessor and thereby reducing the planning and tracking effort by > 20%.
- Phase II of GenAI solution development and deployment is in progress.
ISACA Now: What might next steps look like?
The results from the Pilots have been very encouraging. We are rapidly scaling up our AI/gen AI development and usage across our clients and vendor partners. Considering the ever-changing landscape of AI / generative AI, we are working toward scaled industrialization and measuring the outcomes through a set of RAI metrics across our delivery projects.
ISACA Now: Did the CMMI Performance Report assist in measuring your progress with the new AI integration? If so, how?
The CMMI Performance Report is one of the primary sources of benchmarking on which Cognizant relies. The Performance Report provides a detailed and insightful analysis of the performance of ML5 organizations, which aids in benchmarking and planning for areas of improvement.
The Performance Report also provides insights into the domains being adopted across the industry, which feeds into the strategic decisions made by the organization.
The report also finds references in the RFPs provided by Cognizant, showcasing the differentiator Cognizant brings in with CMMI and GenAI adoptions.
ISACA Now: What advice would you offer to others trying to integrate AI into their CMMI adoption or generally into their business practices?
When CMMI was introduced, achieving the highest level of maturity in CMMI—ML5 (Optimizing) represented a significant strategic advantage. But in today's highly competitive market, it has become table stakes, a baseline requirement that organizations use to demonstrate their capabilities and maintain relevance in the market.
In this context, companies should consider how they can elevate their use of the CMMI model through emerging and advanced technologies like GenAI to strengthen the deployment of CMMI practices and unleash new possibilities across the software, product and service development lifecycle.
To offer some examples:
- The Cognizant Project Risk Profiler can generate likely risks for the project based on its context and demographics. This can augment the Manage business resiliency capability area.
- The Cognizant Knowledge Assistant can strengthen the engineering and developing products capability area. It helps the development and services team find accurate and contextual guidance on architectural patterns, technical solutions and coding guidelines.
- To aid the Planning and Managing capability area, one will be able to use the Cognizant Estimation Assistant (currently under development), which will assist the project manager in making accurate estimations of project size and effort by providing suitable templates, appropriate benchmarks and learnings from past experiences.
