I recently had the opportunity to undertake the Dare to Lead™ course based on Dr Brené Brown’s work. The course is a ‘call to courage’ for leaders to ‘take off their armour’ and embrace vulnerability and trust to enable better conversations, genuine feedback discussions and deeper relationships.
After the course, I started thinking more about what it means to be a leader in the water industry now, and, more specifically, about leadership in the emerging world of Artificial Intelligence (AI).
The fact is, AI is arriving faster than organisations can adapt, making leadership more essential than ever. In the water industry, decision-making is particularly important, as it can carry uncertainty, affect long asset lifecycles, and have significant public consequences.
Most leadership themes in an AI world are focused on continuous reinvention1, adaptability, mindset and behaviour change, embracing transformational change and how to harness AI’s potential. To quote Harvard Business School Professor Karim Lakhani, “AI won’t replace humans—but humans with AI will replace humans without AI.”2 Agree or not, either way, AI has become the new space race. These topics provide valuable insights and are certainly worthy of discussion. However, there is a missing piece here.
I can’t help thinking about the human edge.
Although AI can mimic human language and behaviour to an incredible degree, it lacks the human insight needed to handle complex emotions and behaviours. The hard work of leadership still matters. AI cannot set an aspirational vision, build trust and loyalty, bring stakeholders to a common path, make tough decisions or hold a team accountable. And what of professional judgement?
Harnessing AI to improve decision-making, business intelligence and team dynamics can provide a leadership edge, but AI also has pitfalls to avoid and limitations to understand. As technical knowledge becomes more accessible, emotional intelligence, professional judgement, curiosity, connection, trust and the ability to ask good questions are all human traits that are increasingly valuable.
Do we trust AI or do we trust each other?
Viewed through this lens, AI creates a trust problem. Trust in ourselves, our colleagues and clients is a fundamental requirement of a quality engineer. In stormwater work, this can result in machine-provided answers that look convincing but can still be wrong. More broadly, when leading a team, it can result in unintended erosion of trust and loyalty when wielded irresponsibly.
Trust requires vulnerability, so when your AI friend is waiting right there, ready for a prompt, the temptation is to sit inside a bubble and trust a tool’s answer, rather than reach out and ask for more information or support.
As a leader responsible for mentoring junior engineers and scientists, I am always encouraging my team to question and to trust their instincts and their knowledge while honing their skills in parallel with using AI. There is no point in AI making anyone feel insecure in their abilities; they only need to ask it to do something that they are competent in to see how limited it is in many situations.
While I don’t believe AI will replace engineering jobs, the job description is changing before our eyes, making trust and connection at work more important than ever. We need to lean into the vulnerability of being willing to ask questions, gain support from other people and take leaps despite uncertainty. From experience, I always feel better and learn more by workshopping a viable solution with a colleague or team than I do when prompting AI for validation.
Transparency is non-negotiable
At Rain, we’re actively engaging both non-generative and generative AI as a tool to complement our day-to-day work. Supported by an AI Policy, we are learning just what AI tools can, and equally important, what they can’t do.
Leadership requires setting expectations around transparency and accountability with our colleagues, clients and the public while leading by example. A ‘daring leader’ leans into vulnerability and is willing to create an environment where people can experiment while being encouraged to challenge outputs and put their hand up when something hasn’t worked.
Deep thinking still matters
We’re finding that we can rely on AI to assist in tasks such as analysing large amounts of data, automating repetitive work, providing the outline of a report, and serving as a fast source for useful programming scripts. This frees us up to apply the deep thinking we’re known for when finding solutions for our clients’ water management needs.
Where we’re not relying on AI is when we need to follow a complex set of inputs through to a conclusion. Where professional judgement matters, where significant stakeholder and community inputs are required, and where uncertainty and deep thinking intersect. This is where our clients look to us to provide guidance. In our experience, AI currently falls short in these scenarios.
Accountability creates leaders
Another aspect of vulnerability is accountability. As a leader, I need to rely on my skills, knowledge and judgement. When using AI, we need to think about accountability when checking its outputs and analysing what it produces. You can delegate work to AI, but you can’t delegate responsibility for the outcome.
Our clients want us to lead by providing solutions and insights developed through deep thinking. They do not want to see repetitive AI-generated responses and summaries arriving in their inboxes. It might be quicker for AI to write a report, but at what cost?
As leaders, we need to be alert to truly investing in ourselves and our young engineers, to mentor and coach and provide valuable feedback on how to use AI sustainably and authentically, and lead with accountability in mind, for ourselves and our teams.
From this vantage point, we need to empower our people, align behaviours with values and create an environment of curiosity and accountability.
Leadership and ethics
The ethics of AI can also be viewed through a vulnerability lens. I find it interesting that our industry isn’t talking about ethics more often. At the recent Stormwater Victoria conference, a panel convened on ‘AI in Stormwater: Risks, Rights & Real-World Value’, however, no discussion on ethics occurred. The panel covered a range of topics and ideas, but not this one.
I have many questions that I’m willing to admit I don’t have answers for yet, and I’m sure many others do too. Such as: Where do we draw the ethics line? Do we have enough water to run AI data centres? If I were asked to do a water analysis for a data centre, could I do good work there? How much AI use is too much in the context of gaining experience through the process of struggle and inquiry?
Leadership, vulnerability and courage
As I integrate my insights from the Dare to Lead™ course, I can see that the hard work of leadership requires vulnerability to purposefully lay the foundations for working with AI in our industry. Cultivating the next generation of water leaders in an AI world requires us to foster trust, empower our teams and align behaviour with values. Let’s be purposeful about the traits we impart in the future leaders of the water industry, such as curiosity and courage.
Vulnerability requires courage – both to know and not to know. It takes courage to speak directly to a client about risk, to give feedback and have difficult conversations, to stay the course on an aspirational vision, to hold yourself and others accountable, or to lead stakeholders and communities through significant uncertainty. Vulnerability is the key skill AI will never be able to replace, which makes it a skill worth developing in ourselves and those around us.
1Leadership in an AI-Enabled World | Harvard Business School AI Institute
2AI Won’t Replace Humans — But Humans With AI Will Replace Humans Without AI