For decades, successful business leadership has relied on data, and as a whole, decisions based on data have been proven to drive superior results. Recently, AI in strategic decision-making has been changing the dynamics – first by collecting more data, then by delivering richer insights in a more timely way. And now that executives trust it more and more, AI is beginning to directly manage strategic decision-making.
Traditionally, the decisions themselves were seen as too important to be left to machines, yet a recent study from Oracle reveals that decision-makers are struggling with overwhelm. Decision distress, meaning regretting or questioning a decision you’ve made, has affected 85% of business leaders in the past year, and 74% say that the number of decisions they need to make daily has grown tenfold over just the past three years.
It’s not that they don’t have data. In fact, 70% say that there have been times when they’ve given up on making a decision because the data was overwhelming, and 86% say that the amount of data is making it harder to come to a decision, not easier. As a result, 70% of business leaders claim they’d prefer to have a robot make decisions for them.
But do we really want AI to make decisions for us, or is that just a cry for help? And even if we do mean it, should thought leaders and solution providers discourage us from going down that route?
Only Humans Can Make Reliable Strategic Decisions
One school of thought maintains that AI in strategic decision-making has an important role to play in the process of coming to a decision, but it shouldn’t make the final call. AI doesn’t know which questions to ask, can’t imagine the unexpected, and doesn’t know how much weight to give to different factors in the decision-making process.
This is certainly the opinion of Omri Kohl, CEO Pyramid Analytics, a leading decision intelligence platform that has rolled out extensive AI chatbot functionalities over the past year. “Every time we talk about AI, everyone starts asking the big question: Will AI replace humans? My answer is of course not, at least not when it comes to making critical decisions. GenBI is designed to augment human intelligence, not replace it,” he says.
“AI is incredible at processing data, spotting patterns, and making predictions based on these findings. But it doesn’t have intuition, nor does it understand the nuances of your market or the complexities of your company’s strategy. That will always be left to the humans. The real magic is when the strengths of AI combine with our all too human creativity, experience, and judgment.”
Sure, AI can deliver the insights that you need to weigh up your options, but it’s up to you to decide which insights to look at. What’s more, if something seems a little off, humans are far more likely to pick up on it than an AI system.
AI Can Compensate for Some Human Weaknesses
On the other hand, humans can be terrible at decision-making, especially when we struggle to make sense of the data at our fingertips. We’re inclined to follow our gut and make decisions based on intuition, even when we think we’re taking a scientific and rational approach. We’re easily affected by confirmation bias, overconfidence, and groupthink.
Sometimes we’re faced with data that points to the best decision, but we ignore it to focus on the data that matches our preferences. This is where AI in strategic decision-making can come in, turning the mass of data signals into clear, impossible-to-overlook projections and directions that break through the bias wall.
“With so much information available, it is almost impossible to absorb it all, let alone analyze it and see how it affects your company,” explains executive leadership coach Divya Parekh. “AI surpasses conventional methods to accumulate vast reservoirs of data at extraordinary speed to provide insights and trends that might stay hidden.”
Human decision-making can also take far too long, resulting in missed opportunities and risks that escalate into incidents. AI speeds up the process with incisive insights and predictions that cut through the dithering.
AI Can Make Things Worse
As data teams frequently remind us, AI models are only as good as the data they’re pointed to. If your AI model draws on skewed data, it could produce terrible decisions that appear to be rock-solid, without anyone – human or machine – questioning them. Putting a human in the loop wouldn’t be much help in these situations.
Sometimes, AI in strategic decision-making and GenAI add more noise instead of helping reduce it. This is particularly problematic when decision-makers are already overwhelmed by too much noise and too much information. AI can also exacerbate bias, especially if its outcomes aren’t transparent and final decision-makers aren’t told about how the AI reached its conclusions.
In a report on using AI for intelligence briefings for governmental decision-makers in the UK, Megan Hughes and her fellow researchers at the Centre for Emerging Technology and Security (CETaS) warn that “the use of AI could both exacerbate known risks in intelligence work such as bias and uncertainty, and make it difficult for analysts to evaluate and communicate the limitations of AI-enriched intelligence.”
The Decision or the (Wrong Kind of) Data
While the Oracle study cited above shows that business leaders dream of handing all their decisions over to a robot, it also indicates that they know the real solution: trustworthy data.
While 97% want help from data, 35% don’t know which data or sources to trust, and 77% believe that the dashboards and charts that they have access to don’t sufficiently relate to the decisions they need to make. Close to three-quarters believe that only IT professionals and data scientists can put data to good use.
We also know that humans can make excellent data-driven decisions – as long as we get the right, reliable, and timely data insights. Essentially, business leaders are dying of data thirst while receiving water through a firehose. The solution isn’t to turn off the water entirely and rely on gut instinct, but to deliver it through a straw instead.
The best way to use AI in strategic decision-making is for surfacing the right data at the right time. This means utilizing AI not just to find data, but as an “interpreter” that converts data into relevant insights and pushes them when decision-makers need them most. AI can also serve as a simulator that models potential outcomes so that business leaders can compare the impact of various decisions.
Successful Strategy Requires Human-AI Data Collaboration
AI has an important role in AI in strategic decision-making, helping business leaders make informed choices without taking over the process. Bringing in the right data-based insights at the right time, instead of a flood of data signals, can stop the madness that’s overwhelming decision-makers. Using AI in the right ways can support them to resolve dilemmas and feel confident in their conclusions.
