A 90's action movie introduced me to Artificial Intelligence where machines were charged with aiding and protecting their owners. In an expected twist, AI predicted the only way to prevent humans from causing our own extinction was to sacrifice many of us.
Movies are made for entertainment, for excitement. But even in the real world, the fear of the unknown (or fear of the misunderstood) guides our decisions and actions.
20 years after watching this movie, rather than holding the lead role, it turns out that Artificial Intelligence (AI) is more of a supporting function. There is so much curiosity around AI; people want to figure out how to use AI yet there is so much uncertainty, doubt, even skepticism.
As the host of What I Wish I Knew, I’ve had the pleasure of speaking to a variety of leaders across multiple industries and AI inevitably comes up as people’s fascination grows with it.
Further, I watched the very first What I Wish I Knew episode where Joel Shapiro, Varicent’s Chief Analytics Officer, was interviewed for his deep knowledge of data analytics, data modelling and Artificial Intelligence / Machine Learning.
In this blog, I'll take the insights I have gathered from our guests and explore the questions we all have about AI:
- What Are the Stumbling Blocks When It Comes to AI?
What is Artificial Intelligence | Machine Learning?
Joel gave a universally relatable example: Netflix uses AI to recommend the next video based on what you’ve already watched.
The official definition though? “The capability of computational sophistication.”
AI is a series of sophisticated computing techniques that teases out trends in data and phenomena so we can understand what's likely to happen next. Essentially, taking what’s happened in the past to predict the future.
Why is AI Such a Revelation for Business?
In the past we needed PEOPLE – lots of people to work with information, with data. And not just any people.
People who are interested in sifting through spreadsheets and larger-than-life files. People who are able to amalgamate what they find, and hopefully pull out trends or insights.
Can you imagine those talented, detail-oriented people spending time to give one person their individualized recommendations, like Netflix does? There would never be enough time EVER to do something like this.
Artificial Intelligence Machine Learning (AI/ML) works similarly to how humans work and think. But it is superior in that it can aggregate data and determine trends in a fraction of the time and effort it has taken us in the past. Given any number of unique situations, it uses complex probabilities to pinpoint possible outcomes.
In short, AI makes us tremendously efficient. We can skip the heavy data-sifting work and go right to the decision-making stage.
For example, consider your competitive landscape. Imagine you and your competitors were neck and neck in product development. Your competitor has no access to AI/ML. But you use AI/ML to farm your customer data, including buying behavior, product usage, and other relevant trends.
In moments, you could have this information and the probable outcomes based on the different scenarios you are considering. You can then determine the ideal customer, the ideal vertical, how to more effectively cross sell. In this scenario, it can also identify areas that are low probability – verticals or ICPs to avoid.
AI has allowed us to save time and pull increasingly reliable insights from data. With this newfound power, we can place strategic bets more confidently.
Can you imagine how much more competitive you would be if you could access AI-generated insights?
How Can I Use AI in My Sales Organization?
In past episodes of What I Wish I Knew, business use-cases were discussed to understand how AI can help answer questions like:
- How likely are we to hit our forecast with the current pipeline and current sales team?
- How can we make sure the right sellers are selling into the right accounts and prospects?
- Will this SPIF be effective?
- Which sellers are likely to leave?
Interestingly, in every situation, Joel's response was the same.
By leveraging AI-generated insights, we'll have a valuable head start in determining the next best actions that are most likely to lead to success. Once armed with this information, you'll be able to make data-driven decisions with confidence:
- Executives place sellers where they will be most likely to succeed: product mix, geography, account size, or industry
- Sales Managers and Sellers spend their scarce resources where it will have the biggest impact
- Just like Netflix, past SPIFs can predict the outcome of new SPIFs
- Once you know which sellers are likely to leave, determine the course of action to retain the seller or not
You’re Interested in AI Now, Aren’t You?
Where do I start? This is the question I’ve heard again and again from leaders who are curious but don’t yet have a fully baked plan on how to approach AI.
Here are Joels’ recommendations to be successful with your data strategy and AI/ML:
- Know what problem you want to solve, the questions you want to answer, or what opportunities you’re trying to uncover
- Layer AI on top of your situation
- Run many tests and scenarios; these are fuel for AI
There Are Also Stumbling Blocks When It Comes to AI:
- Leading with tech or investing in AI for the sake of investing in AI.
- Having little or no understanding of the problem you’re solving or opportunity you're driving towards.
- Over-confidence with AI in the early days. AI models takes time to learn and they will improve over time.
- Understanding that the “model does not speak for itself.” Data still needs an advocate to tell the story to support decision-making.
Joel said something that resonated with me: “AI isn’t meant to replace people, but supplement their judgement, supplement their business, enabling business decisions to be made better, easier, and faster.”
Although curiosity grows, some still feel trepidation and reluctance to put full faith in AI and in data.
That being said, things haven’t changed so much. Although AI is blindingly fast at unlocking insights that were previously unattainable, the next steps are the same as always. Opportunities are evaluated, risks are assessed, and decisions are made – by people. Better informed people.
Watch Joel's full What I Wish I Knew episode for more timely insight into unlocking the power of AI.