From the moment we all had our first magical interaction with ChatGPT, the past year has been dominated by curiosity about generative AI. My first ChatGPT moment was laughing with my wife about the creative excuses it generated for why we couldn’t perform our household chores…. On a more serious note, I’ve observed revenue teams getting deeply curious about ChatGPT’s impact on the most important business process in the enterprise.
- Which tasks is AI best suited to streamline and automate?
- How is it going to impact my work on a daily basis?
- How will this change roles and companies?
But so far, there have been more questions than answers. This phase is common for new technologies – it takes time to digest the potential impact of a new technology and incorporate it into our lives.
Now, the curiosity window is quickly closing — especially for companies that want to be at the cutting-edge of AI. In 2024, the name of the game is habitual use and value: shifting from GenAI as a curiosity to GenAI as a daily necessity.
While this transformation may be new in the Generative space, we can draw inspiration from the history of another subcategory of AI: Predictive.
Charting the growth of Predictive AI
Five years ago, CROs were curious about Predictive AI.
They wondered if it could help them forecast more accurately. In these early days, the ability to pinpoint revenue flow and monitor microscopic interactions was still forming. Some teams dove in. Others sat back and watched.
Fast forward to today, and CROs check Clari Pulse on a daily basis as end-of-quarter approaches. They can’t imagine life without the visibility Predictive AI gives them.
And they’re not alone.
Revenue-critical employees across many orgs use CRM Score as part of their daily inspection and forecasting workflows.
Predictive AI has transformed:
- From a curiosity to a necessity
- From the C-suite to the entire org
- From stand-alone features to integrated workflows
GenAI is certainly unique as a technology, but the transformation we saw with Predictive AI gives us a blueprint for making the leap to habitual use and value.
The 2024 game plan for GenAI
How did Predictive AI chart its path to daily use? It wasn’t by accident.
Seeing the impact of predictive tools, revenue leaders embedded Predictive AI into their cadence. They did this by designing specific moments in the course of a week, month and quarter where AI played a role in a critical business process (in this case, calling the forecast).
As today’s leaders look to the future of AI, it’s important to think beyond an AI investment strategy. Alongside access and training, there’s a need to build habitual use among all revenue critical employees.
For this, let’s turn to the science of habits and how to form them.
Understanding the “habit loop”
To guide our thinking on AI integration, we can draw inspiration from one of my favorite books on habit formation– Charles Duhigg’s The Power of Habit.
The core concept of this book is what Duhigg calls the “habit loop.”
The “habit loop” is a predictable sequence that every habit follows. It consists of three parts:
- Cue: The trigger that sparks a habit.
- Routine: The automatic behavior that follows.
- Reward: The tangible benefit that reinforces the habit.
As Duhigg puts it, “This is the real power of habit: the insight that your habits are what you choose them to be.”
Habits + AI
How does the “habit loop” apply to AI?
With the habit loop framework, we can turn AI adoption from aspiration into a scientific process. We can integrate GenAI into daily workflows. We can predictably build AI habits into every corner of the revenue process.
To illustrate, let’s look at how the habit loop would play out for a common sales use case — following up on customer meetings.
Cue: A sales meeting ends.
- Without AI. The rep relies on memory or manual CRM reminders to send a follow-up message. Over time, missed follow-up routines lead to slipped deals. Time spent re-gathering information prevents other revenue-generating activities from happening. These lead to revenue leak.
- With AI. The rep gets a notification in their normal flow of work including a summary of what was discussed and action items committed to. The platform tracks follow-up, creating a level of accountability. These data points roll up into Predictive AI for inspection and forecasting, closing the loop of the revenue workflow, minimizing slipped deals, and preventing revenue leak.
Routine: The rep produces their follow-up message.
- Without AI. The rep starts from scratch or uses manual templates. Message quality depends on the rep’s capacity and writing skills. Action items and stakeholder updates are manual.
- With AI. After every meeting, the rep uses AI to send an auto-generated follow-up email (that they can edit as needed), generate action items, and update relevant stakeholders and fields in their system of record.
Reward: The deal gains momentum.
- Without AI. Delays or missed follow-up messages slow down the sales cycle. This backs up the rep’s pipeline and creates additional drag on future productivity.
- With AI. The rep performs high-quality follow-up for every meeting in a matter of minutes. Deals close faster, and the rep allocates saved time to other high-value tasks.
Will you outperform competitors with AI?
My prediction for 2024 is simple.
We will see massive variation in how much value businesses are able to capture using AI. Teams that install habit loops and drive daily GenAI use will realize serious productivity gains. Teams that stay in the curiosity phase will fall behind.
Where will you be?
P.S. Over the next few weeks, I’ll be sharing a series of posts on AI adoption. In the next post, we’ll dive into identifying areas of your revenue process that can be improved with AI. The priority: finding the biggest sources of revenue leak that AI can plug. Stay tuned.
Learn more about Clari’s AI suite, purpose-built for revenue, here.