Artificial intelligence (AI) is changing the world according to the popular press and the statements of tech CEOs in the last year. There is a lot of discussion about the impact of AI on all areas of business. This post is about how AI impacts program management.

As program managers, we build our expertise in a certain domain, technology, and industry and the bulk of our time is spent managing programs, which align that expertise with organizational requirements.  Some aspects of this management become predictable and repeatable over time-which is usually a trigger for automation and potentially AI.

While the field of AI is large, much of the recent interest is around generative AI (GenAI) after the advent of ChatGPT in late 2022. GenAI has been useful in multiple applications including with answering questions (“how do I?”), summarization (“what are the key aspects?”) and a sliced view (“what at the top 10 issues in this project?”). While the possibilities appear endless, AI can be valuable only when it is relevant, which means it must learn from and refine what is existing and available.

The impact of AI on program management

According to a report on AI in the global Program Managemen Market by MarketsandMarkets, AI will help in streamlining processes, improving efficiency, and mitigating risks. As a result, the market for AI in project management is expected to double over the next five years. The report indicates that by utilizing AI, project managers can improve project outcomes, reduce costs, and increase efficiency. For example, project managers can deploy AI-based solutions to automate routine tasks. This can improve communication while freeing up team members to focus on more effective project delivery.

Businesses need to develop a complete view of the challenges and implications of adopting AI-based solutions for program management. Before implementing AI, they must understand the increased threat of data to leaks and cyberattacks and the accessibility of project management tools on mobile devices which makes data assets more vulnerable. This is particularly important in highly regulated industries.

Regardless, while there is no one-size-fits-all answer, the growing use of AI is expected to help in all stages of program management such as planning, execution, monitoring, and control. AI-powered software can be used to predict project duration, spot potential delays, and recommend different strategies based on historical data. AI can also be used to find areas where more resources will be needed during execution, identify probable problem areas, and modify plans accordingly in real time.

GenAI and the successful project manager

The Project Management Institute Talent Triangle is a framework to help project professionals understand the impact of GenAI, and the skills and competencies that must be acquired and improved to achieve success. There are three areas which define the successful GenAI mindset of a modern project manager:

  • Ways of Working – Method of working where generative AI can help the team meet expectations, but the accountability will be with the project manager in the type of questions being asked, safety of the answers, and the decisions made based on those answers.
  • Power Skills – The interpersonal skills for which AI can be an effective tool in stakeholder communications. Defining the context, purpose, audience, and scope and structuring the response with continuous revision will help provide a concise approach.
  • Business Acumen – Understanding the macro- and micro-influences and having the domain-specific knowledge to align projects with the big picture. AI can become a coach in identifying the problem, gathering the data, generating the solution with human in the loop where the system will interface with a person for feedback and inputs.

With AI still in the early stages, program managers need to be aware of some of the challenges when using AI. Here again, data quality and availability are crucial considerations along with AI model selection and integration, ethics, security, and privacy. Using a human-in-the-loop approach and training to couple intelligent automation with human oversight and feedback will help mitigate the concern areas.

The human in the loop

It is important to note that while AI can excel in repetitive and data-driven tasks, human-centric skills such as decision making, emotional intelligence and adaptability will be key to the program manager’s contribution. The value of program managers will be based on their ability to create context and provide meaningful insights, specifics and strategy which are not repeatable. Last but not the least, program managers can work with teams and leaders in a nuanced manner to provide a trusted relationship – something that is hard for AI to do.

Just as new technologies relevant to Cisco’s business are continually integrated into products and solutions, our business operations teams are looking into collaborating with other teams on the use of AI tools in program management. Stay tuned for further updates.



Padmini Sridhar

Senior Engineering Program Manager

Global Busincess Operations