Debunking sales AI myths

On top of all of the noise in the market about AI, revenue leaders are confronted with having to debunk common misconceptions that have created confusion and misunderstanding about artificial intelligence among their peers and teams. Below are some of the most common myths and their realities to equip revenue leaders for these conversations. This will be critical as revenues lead the charge to the AI-first enterprise, reimagining how their GTM teams operate, engage customers, and drive growth in the modern AI era.

Myth: AI will replace sales professionals entirely

The convergence of advanced machine learning, natural language processing, and predictive analytics has created unprecedented ways for GTM teams to operate with precision, personalization, and scale previously unimaginable. AI shines, in particular, with challenges that could not have been solved at human scale. 

This is the case when thinking about creating a tailored POV for every account, and the amount of time, complexity, and skill required to gather intelligence across thousands of sources, synthesize into something relevant to the customer, and then contextualize it to your GTM motion and value framework. Doing this for one account is hard. Doing it across an entire book of business where every account POV is always current and relevant 24/7 is only possible with AI.

In this way, AI augments human capability rather than replacing it. Successful Sales AI enhances relationship building, strategic thinking, and complex problem-solving abilities that remain uniquely human. While portions of work will get replaced by AI (e.g. manual, time-intensive, routine, and repetitive tasks), this type of automation frees up GTM team time to focus on higher value work that drives customer success and business results.

Myth: AI must solve everything or it’s not valuable

There is no AI panacea, and it’s unlikely there will be one. Because AI doesn’t have all of the context that a human has, asking it to do everything is a failing mission. Instead, the most impactful AI technologies are ones that are purpose-built to improve particular Sales motions and processes. With this in mind, Sales AI should be deployed to solve specific priorities or challenges to deliver specific outcomes, with guardrails to ensure focus, drive results, and minimize risk. 

Myth: AI implementation requires extensive technical expertise

The best Sales AI platforms are easy to use and require little if any training on behalf of users. They offer intuitive user interfaces and pre-built integrations that minimize technical complexity for both users and administrators. 

Myth: GTM teams have to be prompt engineers to get value from AI

While this is often true of large generalist AI tools and legacy tools where AI has been added as an afterthought, AI that is purpose-built for GTM teams makes it easy for users to get quick and lasting value. Because these solutions are designed around how GTM teams work and what they need to be successful, they map into existing GTM motions, and both leverage and enhance existing frameworks and processes to make working with AI familiar to Sales users. 

Myth: AI produces biased or unreliable results

Well-designed AI systems with proper governance frameworks generally produce more consistent and objective results than purely human-driven processes. Modern AI platforms include bias detection and mitigation features, while human oversight ensures appropriate validation and adjustment of AI-generated insights and recommendations. The reliability of AI tech is dependent on the data it is programmed to access and the methods of that access and verification. Best of breed AI solutions deliver unmatched recency, quality, and scope of data sources to deliver always-current, relevant, and comprehensive insights. 

Myth: AI doesn’t deliver enterprise value today

While this is true for many of the large generalist AI tools, AI solutions that are purpose-built to solve the challenges of a clearly defined ICP are delivering value to enterprise customers today. Reviewing customer case studies, talking to existing users, and trialing AI technology in your own environment can reveal and prove out the value of the AI to your business prior to committing to a commercial partnership.

Next Steps

Leading CROs are already deploying AI and achieving enterprise value, like to build org-wide competency around account intelligence to unlock value selling at scale. These CROs are enabling their teams with deep knowledge about customers—their priorities, needs, and challenges, and how they uniquely solve them—to ensure relevance at every stage of the customer lifecycle to drive both business and customer success today.

With ubiquitous access to this AI-enabled tailored point of view (POV) for each customer, GTM teams show up smarter than competitors, speak in the customer’s language, confidently lead with value, and attach to their top priority—to win. And customers win, too, with a consistent, world-class experience focused on their success in every interaction.

Revenue leaders looking to kickstart their organization’s journey to the AI-first enterprise can start a trial of Poggio to arm their GTM teams with tailored POVs to show up smarter than competitors and win.