Revenue leaders are faced with a hard truth.
You're either developing an AI strategy, or you're signing up to get left behind.
But with all the noise around AI development, it’s tough to decipher between high-impact business technology and shiny distractions. In the coming years, B2B revenue teams will invest millions in AI that doesn’t move the needle.
In this letter, let’s shed light on 3 harmful AI myths and how you can combat them. Use this guide to refine your AI strategy and chart your path to a legendary revenue career.
Myth 1: Revenue Teams Should Focus on Generative AI
The day ChatGPT launched, 99% of AI chatter shifted to Generative AI.
Honestly, this isn’t surprising. Of all the types on the market, Generative AI is the easiest for revenue teams to see and experience, so it dominates the conversation. But an AI strategy focused exclusively on Generative AI misses the revenue-boosting potential of other AI types.
Descriptive AI tells you what has happened in the past. It summarizes and suggests next steps so you don’t waste time reviewing calls or tracking down emails. While Predictive AI tells you what will happen in the future so you can make decisions with certainty. With Predictive AI, you can pinpoint deal health and quarterly forecasts.
Instead:
Create a well-rounded AI strategy, integrating Generative, Descriptive, and Predictive AI. Equip your teams with the best tools to create opportunities, convert them into prospects, and close deals with precision.
Myth 2: AI Integration Will Win the Day
Most revenue leaders are scrambling to bring any AI into their workflows.
But there’s a severe problem with this approach. All of your competitors are scrambling to do the same thing. In today’s market, base AI models are commodities that are available to everyone. To win the day, you need more than a plug-and-play AI solution.
What do you need?
Revenue teams who want to refine the revenue process and deliver breakthrough results need to focus on (1) the quality of the data provided to their AI models and (2) how data is integrated into various revenue-specific workflows.
Instead:
Focus on your intentional integration. This requires looking beyond off-the-shelf AI models. It requires thinking more broadly about your proprietary data sources and how you’re weaving AI into every fabric of your team’s day.
Myth 3: You Should Leave It to the AI Experts
AI is complex and advancing at a blistering pace.
Should it be left up to the experts? Not if you’re a revenue leader looking to boost your bottom line and grow a legendary career. There’s no need to sit on the sidelines when you’re the one who knows revenue inside and out.
In fact, I’d argue AI strategy has transformed into a revenue leader’s top responsibility. The strongest leaders will take extreme ownership of in-depth integration and champion AI tools throughout the organization.
Instead:
Grab the wheel. Start by tightening collaboration with your technology partners and casting a compelling vision for your team. Don’t wait for someone else to take the lead or set the narrative. This is your revenue workflow. Own it.
Looking to master your AI strategy?
Don’t stumble on these harmful myths.
- Revenue Teams Should Focus on Generative AI
- AI Integration Will Win the Day
- You Should Leave It to the AI Experts
Instead, cut through the noise and focus on what really matters — growing your business. Do this, and the rest of your AI efforts will fall into place.
Keep leading,
Andy Byrne
CEO, Clari