In part two of this series, we discussed two options leaders face when it comes to Generative AI: leading with hope or fear. I hope you choose hope! Now, let’s talk about how to set some realistic expectations on how to move forward with that mindset.
In 1984, some of the same realities were true for technology leaders. It’s almost eerie how similar things are from a bird’s eye view. Drew McDermott said:
“In spite of all the commercial hustle and bustle around AI these days, there’s a mood that I’m sure many of you are familiar with of deep unease among AI researchers who have been around more than the last four years or so. This unease is due to the worry that perhaps expectations about AI are too high, and that this will eventually result in disaster… it is important that we take steps to make sure [an] “AI Winter” doesn’t happen — by disciplining ourselves and educating the public.”
If you turn the words “four” into “forty,” this could have been written today and no one would question it. From ELIZA being introduced in 1966, it is mind-blowing that many of our AI solutions are not that much more sophisticated. The 1980s through the early 2000s saw a vast change in advancements compared to early AI.
“AI Winter” refers to a period where AI funding and research slows down significantly. In April of 2023, Built In covered the top drivers of an “AI winter”:
1. Decreased public and company interest in AI.
2. Decreased funding toward AI projects.
3. AI technology not living up to expectations.
In December of 2022, ChatGPT was released to the public. Less than a week later, over one million consumers had signed up to explore Generative AI. Not even a year later, by January 2023, Microsoft had announced a multi-billion-dollar investment into Open AI. It feels safe to say the first two drivers of “AI Winters” aren’t top of the concerns list.
AI is now widely accessible and relatively easy to navigate for the regular not so “tech-savvy” consumer. As consumer use continues to grow, let’s assume the funding and public interest will follow. That leaves one item remaining: AI not living up to expectations is the driver that organizational IT leaders should pay the closest attention to.
If we want to lead our teams into the future that they helped dream up, leaders must be cautious when setting expectations. Just as traditional prescriptive chatbot technology did not eliminate IT support’s existence, neither will Generative AI.
Setting the expectation that Generative AI will remove the need for humans to provide support isn’t backed up by data found in anything other than predictions. Trusting in what actual outcomes are indicating over predictions is the safer bet.
Leaders should pause and rewind in their minds. Maybe it’s five years, ten years or twenty years. Think back to being new to the service desk role. How many times did a new technology arrive that impacted the business? The answer is a lot, regardless of how far we rewind in our minds. The constant through that change? IT support is still around.
Poorly set expectations for the impact of Generative AI not only pose a risk of an “AI Winter,” but to our organizations, it means inaccurate financial forecasts, unwarranted concern about job security and possible missed commitments to customer experience advancements.
Human connection, empathy and the psychological need for relationships are things that have stood the test of time. There is no Generative AI that can replace these things. Outside of first responders, educators or medical professionals, it’s hard to think of an industry of professionals who provide these things at a greater rate than IT support teams.
Let’s pretend that we wake up tomorrow and Generative AI capabilities have become so advanced and cost-efficient that we can replace every IT support function. In this hypothetical reality, the question leaders should be asking isn’t: “How quickly do I turn it on?” but rather, “What is the true risk to my organization if I do?”
Generative AI is here to stay, that much is clear. When it comes to the business impact it will have, it feels like it’s still too early to call it. Leading your support team into the unknown with intentionality will enable hope. Leading passively will enable fear. Be transparent. Give your support team a seat at the table and set realistic expectations. Hope or fear for the future — leaders, the choice is up to you.