Sold With AI - Edition One (Introduction)

AI is knocking on Sales teams' doors. For most people, it is a too noisy a knock. In this edition, I talk about how sales leaders should think about AI. And start making sense of the noise.

To sell is human. Or so we have heard for a long time.

But the age of AI is here. What will happen to selling, and what will happen to sellers? This is a question that is occupying many minds today. Including mine. 

And if I am not wrong, yours.

But before we go on, who am I? And what exactly is the brouhaha about? 

Well, if you know me, I am the founder of Humantic AI, a Top 3 Sales AI for 2023 as per G2. You are receiving this email because you either use Humantic AI, or have at least come across and considered it.

I am someone who spends a lot of time at the intersection of sales and AI. Around 30 hours a day as per my wife, but at least 12 if you ask me. 

I am also someone who got interested in AI 25 years ago (yes, I am not missing a decimal). I then started my first AI startup in 2014. When Forrester named the world's first set of 5 AI startups in consumer intelligence in 2019, my first startup (Frrole AI) was one of them. 

And then, some Emmy winning professor invited me to interview with the Wall St. Journal. And for some reason, they decided to call the AI we built a 'technology that could reshape the world'. (Talk about pressure to perform)

Some people got very excited. And some got quite offended.  The guys over at World Economic Forum got very excited and called it an AI that could end bias in hiring. Those at Vice got offended, and shared their sense of offence quite publicly. Someone over at this small college magazine called Harvard Business Review decided to chime in too. 

Truth be told, I spend a lot of time thinking about this topic. This email is an attempt to synthesize those thoughts and give them some structure. Share those thoughts with you. And hear your take - I am equally excited to learn from your vast sales expertise.

Every month, on the first and third Sunday, I intend to pick up one topic related to the role of AI in sales. Is it for everyone? What is the right pace of adoption? What are the biggest pitfalls? How do you know it is going wrong?  And more. (Note: this is going only to Founders, CXOs and senior Sales leadership only, but if this is not useful for you, go ahead and hit that unsubscribe button. I won’t mind.)

For this first edition, I want to start with the basics. And answer a simple question - as revenue owners, how should we think about AI?

How to think about AI

In many ways, AI is just another technology. Like many before it - Blockchain, SaaS, Web development and so on.

But in many other ways, it is like nothing we have seen before. The closest probably is the internet. And I would say that it would be exponentially more impactful than the internet (just as the internet was exponentially more impactful than computers, or computers than mechanical machines...).

Perhaps a good way to think about AI is to think of it like a nuclear bomb. It is still just a bomb (like many before it), but practically, it is an entirely different animal. I think that could be a good frame of reference.

So should all of us be thinking about AI? I think so. (Unlike the question "should all of us be thinking about AI equally?". That is a much more nuanced question, which I will cover another day.)

However, my hunch is that after the honeymoon period (led by fascination with Gen AI) is over, most will experience the proverbial 'trough of disillusionment' except for a few sectors/early adopters. At least relative to the interest there is today.

Interestingly, when it comes to Sales, I also think that adoption of AI in sales would be led by competitive pressures. In most sectors, there will be early adopters who will be fast to build leverage using AI. While they will face some challenges, they will start seeing results quickly (remember, AI impact is going to be non-linear.)  And all the slow-adopting competitors in their fields will have no option but to respond.

Conversely, it also implies that those who will adopt AI fast will gain a distinct competitive advantage. Provided they can harness its power (which will depend on many factors, something we will talk about later too).

I also think that the right way to adopt AI would be by taking a 'pieces of the puzzle' approach. However, most sales teams would default to a 'beads of a string' approach, which is how they have traditionally adopted all tools and technology. it will not fail, but the results most likely would be sub-optimal.

One costly mistake that I believe was made in the last technology adoption cycle in sales was the mistake of 'skewed balance'. What I mean is that when we adopted technologies that helped us do 'more' (more data - like Zoominfo, or more activities - like Salesloft), we failed to adopt technologies that helped us do 'better'. And that led to the 'modern dust bowl of sales' as Dr. Howard Dover etc. have put it, or the 'tyranny of more' as senior Gartner analysts like Hank Barnes have put it.

With AI, the primary action we should start thinking about should be the one needed against its roboticism. It is AI's #1 trade-off, as many have already started pointing out while using Generative AI. Ironically, no other statement highlights this fact as much as this tweet by Open AI Cofounder and CEO Sam Altman himself - where he is struggling to make Open AI talk to him in a language that he appreciates!

Unless we take action to neutralize it by emphasizing the human element equally, we would end up creating a 10X bigger AI dust bowl in 5 years. Where people stop engaging with AI-enabled approaches because it would just feel weird and mechanical. (A lot of our work at Humantic AI focuses on this area.)

Productivity, or efficiency is the #1 promise of most big-league AI. In its Copilot announcement, the key benefit highlighted by Microsoft is nothing but the ability to complete more tasks during the same amount of time. Unless we balance this improvement in efficiency (which by the way will occur) with improvement in effectiveness, we would end up sacrificing long-term for short-term. And it won't be the first time.

Yin and yang. Day and night. Robots and humans. Balance is the law of nature. And that is how we should be thinking for the age of AI.

Especially for the age of AI.