Overcoming the Human Element in AI-Powered Projects

When OpenAI released its ChatGPT in November 2022, the lofty promises and ominous warnings of how artificial intelligence will change the world had been permeating discussions everywhere, and for good reason.  In the umbrella realm of project management, for example, artificial intelligence promises better project investment selection and prioritization, automation of routine processes (especially in support of project management offices), improvement of project planning and status reporting and virtual assistance capabilities.  AI has also been touted as solutions for project management professionals to automate testing and quality control of deliverables, especially digital tools and software, as well as the promise of accelerating analysis of project management parameters such as risks and issues, with the capability to uncover underlying and hidden factors that may impact a project’s performance. 

At least one company, Deep Knowledge Ventures (DKV) based in Hong Kong^[1], promotes artificial intelligence for investment decision-making. They state on their website, “These machines automate due diligence and give us unique advantages compared to normal human capabilities.”  Of their eight team members, four of them are artificial intelligence bots, aptly named: Fintech AI, Vital, Spock, and Nanotech AI.  AI will likely be sitting in many more seats, figuratively, and in many more companies in the near future.

For all of the bravado of AI, before we become too dazzled or dismayed (depending on which side of this issue you reside), at AI’s potential impact on projects, it is worthwhile to sit back with a skeptical bird’s eye view. After all, as we humans evolved throughout the information age of the mid to late twentieth century, AI can just be considered the latest development in a long series of technological advances driven by the engine of human information input.  Even if every one of the improvements stated above are tangible, how well does it translate to the ultimate outcome?  Organizations around the globe have been trying to digitalize and computerize, some as early as the 1960s and 1970s. Digitization and computerization promised a revolution in productivity through automation, streamlining, and making humans redundant. But the road to a more significant productivity boost has been arduous at best.  One of the primary reasons is captured in the Theory of Constraints (TOC) developed by Eliyahu M. Goldratt, an Israeli physicist turned business management guru.  In his landmark book The Goal, which sold over 6 million copies, he explains the importance of focusing on the right constraints to improve the overall system.  For projects, the constraints are generally not within the technology and tools, but within humans. 

The human factor has always been complex and perplexing. The CEO drama at OpenAI in November 2023 over its superstar project, ChatGPT, is just one sign of a messy future where Ai is relied upon as an anecdote to the human condition.  For AI to make significant headway in improving project performance, here are the top five human constraints that need to be tackled:

1. Inherent Limits – Unlike machines, humans have their built-in restrictions. For example, we can only be productive for so many hours before the need to rest, we need regular nourishment, and we need special care and attention to keep on working. Thus, even with the best AI analysis, dashboards, and reports, if projects require human intervention, then human constraints remain the great common denominator across the board on all projects.
    
2. Knowledge & Learning – Humans are also limited by their knowledge and their ability to learn new skills.  There may be a day in the future in which people can simply download new knowledge, but until that day arrives, project performance is limited by the capability of its people. The “absorptive capacity” or learning acquisition of people can be the bottleneck in any projects that require learning and utilization of new knowledge.
    
3. Motivation & Self Interest – Unlike machines, maintenance required for human to operate at peak performance is much more difficult.  It requires thoughtful ways to drive humans to achieve project goals willingly, as opposed to resistance, which can sap energy from project teams.  At this point in the evolution of AI, it is difficult to envision how AI technology can motivate humans. In fact, AI can be a great de-motivator, as shown in the recent uproar over Sports Illustrated’s use of AI to create articles. ^[2]
    
4. Cultural Incompatibility – With the exception of a few companies, such as the aforementioned DKV, the dominant culture of today’s organizations is not likely to be well-matched for AI influence.  While there will likely be an appreciation of AI and its power to analyze and present data, it is quite another issue for AI to direct people and make decisions. 
    
5. Organizational Politics – Even when individual human constraints are effectively managed, there are still organizational challenges, starting with politics.  There are many factors of politics such as disagreement of priorities, power struggles, resistance from influential stakeholders, hidden agendas, information asymmetry and manipulation, formation of alliances and coalitions, and fear of losing status leading to decision-making paralysis.  Even the best of the AI systems cannot easily overcome human workplace politics. 

For both modest and large scale projects to be ready to embrace AI and leverage its power to the fullest, the investment must not only be in technology and tools, but also in the humans that manage the technology and tools, in order to reduce, or perhaps, even close many of the gaps.  Here are three ways to start now:

1. Be open about the use of AI and its direction. As in the case of Sports Illustrated or Microsoft’s MSN^[3], companies should be more thoughtful and transparent about their use of AI. Since it was first published in August of 1954, Sports Illustrated has been the trusted source for sport news and analysis for almost 70 years.  Is it worth putting all of that at risk with the unannounced use of AI to start writing articles? 
    
2. Create better knowledge management systems. While skills can be learned rather quickly, experiences take time.  Organizations should invest in AI powered knowledge management systems combined with human-to-human mentoring and coaching programs to share knowledge and good practices.  Project managers of the future will likely play a greater role in these areas, disseminating knowledge to project teams and elevating everyone’s performance. 
    
3. Get the people involved. AI can be powerful, and not just in creating reports or analysis of information. AI tools can boost collaboration, problem solving, content creation, and productivity enhancement when used correctly. But it still needs motivated people to apply AI tools and check for mistakes to avoid hallucinations and other pitfalls.  Organizations and their project teams should make commitments to their people on the ethical use of AI, involve and train employees to leverage AI technology, and share the benefits of AI with their teams.
    
4. Create the optimal culture for AI to thrive. As organizations gain trust of its people on its AI journey, companies should strive to find the right balance between the use of AI and people. Perhaps there can be explicit limits on what AI will do, such as creating project schedules or analyze risks, and what AI will not do, such as assigning tasks to people with a thorough review of the schedule and tasks by project core teams. By leveraging both the power of AI and people, organizations can create suitable cultures to achieve higher performance.
    
5. Consider adding AI to the table. One of the most contentious project activities is the prioritization and approval of projects and portfolios.  After all, projects and portfolios can represent significant resource commitments. With limited resources, there will be winners and losers in organizations, and organizational politics almost always comes into play.  Perhaps organizations should invite AI to the table and become one of many evaluators and decision makers. By giving all people an equal role in shaping the data and analytics, AI can be a reasonably unbiased analyzer of project attractiveness.  This can lead to less political infighting and more time to develop algorithms that best advance an organization’s decision making process.

The Pandora’s Box of AI has been opened and there is no turning back. Chatbots like ChatGPT are already being used by millions of people on all types of work, including high stakes projects.  Organizations that fail to adopt AI will likely suffer and lose in the long run.  But while the power of AI tools is impressive, they are often not the greatest bottleneck to the destination of successful project completion. It is us, the humans.  Organizations should start immediately to prepare their people for an AI-powered world.