Relationship between Artificial Intelligence and Leadership

I recently attended the Healthcare Information Management Systems and Society (HIMSS) 2024 conference in Orlando, Florida. As the Global Head of Agile Strategy, I represented Inflectra corporation looking up for learning about the growing influence of information systems in the healthcare space. It was wonderful to see the various improvements in the healthcare space in pre-clinical, clinical, and post-clinical stages of drug development, various healthcare and life sciences spaces like ambulatory care, hospital management, emergency care, neonatal and pediatric spaces, and endless array of devices and software products that support these areas. 

One thing that I saw written in many of the sessions, keynotes, exhibitors, and conversations among the attendees was the influence of artificial intelligence. Unlike many other audiences, these discussions were not just on large language models or generative artificial intelligence but also on deep machine learning algorithms within their line of work. While people talked about training data, prompt engineering, privacy and security considerations, there were only a very handful of sessions that I can count in my one hand that I was exposed where people talked about digital ethics or leadership. 

One of the expert panel speakers at the onset of the conference keynote commented about Steve Polack's quote, "... before talking about artificial intelligence, let us talk about natural stupidity!" History has taught that there have been a lot of lessons learned but we continue to learn the same mistakes due to personal egos, bias, labeling, stereotyping, and plain unwillingness to learn. This is one of the reasons why I even say, "Common sense isn't common!"  Therefore, if we take the evolution of people compared to the growth of technology, people have lived longer in relation to technology and yet lack perfection! Then, how can we expect technology to be perfect? 

This is the fundamental reason why we need leadership. Every time people rush to do something, it is the leadership from everyone that puts the checks and balances required in the processes to ensure the right thing is done. For every change, including but not limited to what artificial intelligence brings, it is not about whether you like that change or not, but it is about the rate at which we adopt it successfully. In a couple of sessions, there were experts referring to cases where the ChatGPT based solution was not successful because there was not a clear business case, and that leadership and AI governance were mandatory for AI to be successful ever. We talk about business case as a strategy document balancing the benefits with the risks and how the strategy aligns with the vision (that is from an "as is" state to the "to be" state). Such a business case is not made up of just plain technical experiments without a solid use case to support the business. 

Furthermore, the closing keynotes focused on how 'advanced technology' does not necessarily mean technical elements alone but require strategic considerations for legality and ethics. Embedded deeply in these thoughts is the need for the leadership (not just the people at the top but also the middle management such as product, project, account, program, portfolio, process, technology, HR, etc.) to partner, engage, collaborate and knowledge-share with multiple stakeholders garnering support for the strategy and vision in the business case. This may additionally involve how to crowdsource fund differentiating between investment and funding schedules while simultaneously managing the in-house talent for capacity, transition, and succession planning! I believe if people are not engaged to lead and manage their processes, technology alone will not yield a solution. And, if we don’t think this way, we are not managing risks effectively and efficiently. Don't wonder why quality suffers in this case!

These thoughts are much more than just focusing on Agile and DevOps thinking as part of AI based experiments baked into iterations and spikes. I firmly believe that the ways of working are integrating two big frameworks in today's digital transformation. This integration involves both the middle management frameworks (like portfolio, program, product, and project) with the software development lifecycle (SDLC). So, instead of getting mixed up with plan-driven, adaptive, and hybrid ways of working that is equally important to both these frameworks, we should focus on "Product Application Lifecycle Management" (PALM, in my mind) that brings the frameworks together using multi-artifact traceability and auditability.  As I always say, enterprise business agility is not shifting left and shifting right alone but it is also about shifting up and down. That is how value flows - both vertically and horizontally. 

As a part-time assistant teaching professor at Northeastern University, I can tell that not every graduate courses in digital marketing, informatics, project management, software engineering, and business schools even mandate a good understanding of leadership. In fact, sometimes, project management graduates can't articulate the requirements of a contract or the procurement guidelines. Having trained many professionals for certifications furthermore outside the teaching engagements, I feel that even these tenured working professionals or those holding Certified Scrum Master can't understand the ingredients of servant leadership. 

We are on the cusp of a major change just like Internet or Telephony made waves once changing the landscape of how we work. We have one more opportunity to write history in leading the AI wave on how we work or will work in future. At this juncture, paying attention only to the technological aspects alone or yielding to comfort zones of known technical tools alone is a sure prescription for failure. If we know the principles of leadership, then, we can develop the right AI based solutions ensuring digital ethical principles like beneficence, non-maleficence, justice and autonomy are protected further ensuring that we monitor the AI's ability to explain itself identifying model drifts and hallucinations. 

Let us join forces learning about leadership first and technology next. Share your thoughts.