AI’s Achilles’ Heel
By Alex Alleyne
I remember the first time I logged into ChatGPT and was blown away by its potential. I ran a number of searches and was immediately impressed by the learning I was able to garner.
With that said, there’s a fundamental premise I hadn’t considered. AI is only as good as the data and modeling it’s trained on: AI models like ChatGPT, which have taken the internet by storm, rely on vast amounts of data. However, these sources are not necessarily qualified or vetted, meaning the outputs are not always entirely factual. It’s like putting a load of ingredients in a blender without any clarity as to what the end result will come out like.
It reminds me of the first time I was running a forecast meeting powered by AI. I noticed my personal forecast was a far cry from the one the AI tool I was leveraging predicted. Once I dug deeper, I found t that my sellers were behind on their CRM hygiene and hadn’t updated their sales stages yet. This meant the AI tool was basing its projections off of ineffective data.
Through all of this, it’s important to remember that even though AI has been on the map for some time, it’s still green technology and we can’t rely on it as a sole decision-maker. Tech giants like Microsoft will continue to drive the technology forward and make promising developments, but at this stage, there’s still plenty of growth to be had.
Balancing Automation and Authenticity
You can’t rely on AI to be your judge and jury, but you can rely on it for baselining and frameworks. For example, when going into a forecast, I often encourage my leadership team to first look at the AI projected forecast.
I then ask them:
- Does the AI projection align with your forecast?
- If yes, why? If not, why not?
The AI forecast can be helpful to provide a baseline for what type of information should be considered for your Sales Managers’ forecast. It encourages them to be more thoughtful about current pacing, closing rates and conversion rates that will have a notable impact on your roll-up.
Where I have found it to be most valuable and trustworthy is for specific use cases like automating administrative tasks. AI tools like Otter.ai can automate tasks like note capturing and meeting summaries, saving a ton of time and increasing efficiency. It’s like having a personal assistant who never gets tired and can tackle those mundane tasks that often eat away at the clock.
This can also play into Sales Enablement. Should you deliver sales training, the session can be recorded with shareable summary notes to distribute to the team as a follow up. Otherwise doing this same activity manually could take 30 – 60 minutes in itself.
The gap is its inability to bring character, personality and authenticity into the customer facing aspect of a SaaS Sales Leader’s role. Could you count on AI entirely to write your emails, communicate with customers and internal teams alike? At this stage, certainly not without being closely monitored. It still has a way to go before it can truly emulate enough humanistic tendencies for you to be able to count on it to take away the majority of your workload.
Directionally, I don’t think it will be too long before it can take on a much heavier lift than it can currently. The pace of innovation is electric and you should certainly embrace the direction of travel versus trying to resist the inevitable.
Sidekick vs Superhero
Accept the current limitations of AI and use its output as a starting point for your decisions, rather than treating anything it outputs as a definitive fact. Think of AI as your sidekick – it can give you valuable insights, but you’re still the one who has to make the final play.
Next week, we are switching gears to a new topic area, by diving into the challenges of being a first-time SaaS Sales Leader and, in subsequent weeks, we’ll continue to explore how to maximize success when making that transition.