“Can we get serious now?”
I love this line from the 2016 movie Sully, where Captain Chesley “Sully” Sullenberger, portrayed brilliantly by Tom Hanks, stunned the participants of the NTSB hearing by pointing out the fatal flaw in their analysis.
If you haven’t seen the movie, Director Clint Eastwood’s fictional (and antagonistic) version of the NTSB used computer models and simulations to show that US Airways Flight 1549 had enough time to safely land at either of two nearby airports after losing both engines to a flock of birds at 2,800 feet, instead of crash-landing in the Hudson River as it did. SPOILER ALERT: They were ultimately proven wrong, and Captain Sully was both vindicated and proclaimed a hero for his decision.
So, what was their mistake? How did the movie version of the NTSB get it wrong? According to Sully, they had failed to take into account “the human factor.”
Like Captain Sully in the movie, I want to ask, “Can we get serious now?” to the crowd of AI fanatics and fear-mongers across the Internet who believe, as some have claimed, that AI may soon replace human Competitive Intelligence (CI) professionals. Why so? Because these poor souls have failed to recognize the importance of “the human factor” in intelligence analysis. They have lost sight of what AI actually is, and what it is not.
Have we forgotten?
A few decades ago, the term “artificial intelligence” was almost universally understood to refer to the science fiction concept of a sentient (i.e., self-aware) man-made computer system. Think of Skynet in the Terminator movies, or The Machines in The Matrix movies. It was a theoretical concept that frankly most understood to be utterly impossible. Since then, AI has quietly morphed into something more believable – software that imitates human cognition (e.g., research, writing, art, etc.), the keyword being imitates.
The term AI has become so commonplace that many have forgotten what the “A” stands for: “Artificial.” That’s right, AI is not true intelligence, but rather a man-made simulation of intelligence. Like artificial sweeteners and artificial turf, artificial intelligence can mimic some of the attributes of true intelligence, but at the end of the day it is not true intelligence. As they say in Texas, “You can put your boots in the oven, but that don’t make ‘em biscuits.”
So, let’s get serious and address this issue of AI and its implications in the world of Competitive Intelligence. Let’s start by addressing what AI can do, and then address what it cannot do.
How can AI help with Competitive Intelligence?
Make no mistake, AI technology has made impressive advancements, and AI tools of today can be incredibly useful for certain things.
One of the most significant strengths of AI software today is its ability to process large amounts of data quickly and efficiently. Traditional CI methods have struggled at times to analyze the sheer volume of information available, but AI-powered systems can sift through extensive datasets, extracting relevant information and identifying patterns that humans may miss. In some cases, AI may even enhance the accuracy and precision of such efforts by minimizing human biases and errors.
AI tools may also be helpful by automating mundane tasks, such as collecting and organizing data from various sources. This has the potential to free up analysts to focus on higher-level tasks such as interpreting results and devising effective competitive strategies.
Natural Language Processing (NLP) algorithms, including Large Language Models (LLMs) such as ChatGPT, are one of the more popular applications of AI today. These can be extremely helpful when it comes to English composition or “word-smithing” in situations where the CI output needs to be in written form.
What are the limitations of AI in Competitive Intelligence?
Despite the above benefits, there are significant limitations to what AI can do in the realm of CI. The main problem with applying AI and machine learning to Competitive Intelligence, as indicated above, is that they are missing the human element – specifically the qualitative analysis and decision-making – crucial ingredients in the intelligence process, where the “what” must be converted into “so what.” But there are other limitations as well.
Obviously, AI systems are heavily reliant on the quality and availability of data. If the input data is incomplete, biased, or outdated, it can lead to inaccurate insights and flawed conclusions. The recency issue is a notable weakness of ChatGPT, which completed its “training” in September 2021 and does not have access to real-time data after that point.
Another problem is that AI and machine learning algorithms thrive on patterns and repetition, whereas competitive procurements change dramatically from one market to the next, one customer to the next, and one competitor to the next. Why? Because all the actors in the process are humans, and humans can be inherently unpredictable. No amount of training can sufficiently prepare an AI to reliably predict when a human actor will suddenly deviate from past patterns of behavior or choose to behave irrationally.
Speaking of things that AI will likely never be able to do, another compelling example is elicitation or the gathering of information via direct person-to-person conversation. This is something that would require an infinite – and ever-changing – library of dialects, idioms, and subtle nuances of verbal communication, that machines may never effectively master, no matter how many resources mankind throws at it.
Conclusion
In our view, when it comes to Competitive Intelligence, the human touch really does reign supreme. Answering the question of whether AI can replace competitive intelligence is as simple as answering the question “What is intelligence?”
If intelligence simply means a large amount of data or even data that has been filtered in specific ways, then the answer is yes. But that is not intelligence. Intelligence, as we have defined it in previous articles, is the analysis of data to derive meaning that informs decision-making. By this definition, it should be clear that this kind of intelligence will always require human involvement.
In order for AI to replace humans – whether in Competitive Intelligence or in any other analysis-heavy field – it must truly break through the bounds of reality into the world of science fiction.
