By 2025, 75% of B2B organizations will use AI-powered sales solutions for hyperautomation, according to Gartner. Are you on board too?

There is keen interest in artificial intelligence (AI) and machine learning specifically for sales management in the B2B market. Gartner’s “2021 CSO Priorities Pulse Survey” shows that investment in AI analytics and technologies is rising.

. It is well known that increasing competitive pressures, lower margins, and volumes of data not being appropriately used are critical drivers for sales management with AI. But other factors are making hyper-automation in sales inevitable.

This article discusses what “sales management with AI” means and how “hyper-automation” relates to it. After that, you’ll learn three other compelling reasons (besides competitive pressure, low margins, and lots of data) why hyper-automation in sales is becoming inevitable.

What do “Sales Control with AI” and “Hyper-Automation” Mean.

Roughly speaking, AI-based applications in sales can do two things: automate sales processes and optimize sales processes. Both relieve the burden on sales staff to concentrate on their core competency, namely serving their customers. The whole thing is done based on complex data-driven analysis recommendations for the next best step in the sales process.

“Automating sales processes” means that a program controls manual processes automatically. An example would be manual data analysis via Excel versus AI-based data analysis through machine learning algorithms. Hyperautomation occurs when collaborative tools automate complete business processes. For sales, such a process might look like the following:

1. automated preparation of historical sales data,
2. AI-based analysis of historical data,
3. making sales predictions about future customer behaviour (predictive analytics),
4. based on the data and predictions, an AI-generated recommendation for action is played out directly to the sales staff (Prescriptive Analytics).

That means that only the last step, the concrete data-based recommendations for action, is visible to humans (in this case, the sales team). And all the steps are taken over by software. Sales reps only have to decide whether or not to follow up on the recommendation.

As in the above definition of hyper-automation, you need digital tools. For the hyper-automation process described in this article as an example, you would need two collaborative tools: An ERP (enterprise resource planning) system as a data source and AI-based sales forecasting software.

Now we come to the optimization of sales processes through AI. To what extent do processes improve with the help of artificial intelligence? In that, it finds hidden opportunities, such as sales opportunities or pricing potential. AI also reduces sales costs, as salespeople focus on the most promising activities. And lastly, AI increases process efficiency (better outcome with less effort).

“Sales management with AI” means that artificial intelligence is used as essential support and information preparation for data-based sales decisions.

Three More Reasons why AI & Hyper-Automation is Becoming Inevitable in Sales.

1. Experience- and intuition-based selling is changing to data-driven selling.

We also wrote a detailed and extensive blog article about this point . However, in a rough summary, we can say that data-based decisions are becoming more critical.

That does not mean that the intuition of an experienced sales manager is worth nothing! Data helps where instinct stops. Above a certain amount of products and customers, even the most experienced salespeople lose the overview. It is therefore becoming increasingly important to include data-based recommendations as a basis for sales decisions. That is how companies discover hidden but valuable sales opportunities.

2. The B2B buyer’s journey is changing.

According to Gartner, B2B buyers spend only 17% of the buying process communicating with sales reps. Does this mean sales will become obsolete? No!

It just means that much of the buying journey is happening digitally: Information searches, product and vendor comparisons, and review research all take place digitally for the most part. Sales come into play as the last instance in the pipeline and, as a result, are also becoming increasingly important.

Buyers communicating with sales have problems they could not solve digitally. These can be complex purchasing structures, for example, or specific product issues. Sales as a consultant are indispensable.

An automated process chain to sales is essential for a smooth B2B purchasing experience. That enables sales staff to respond quickly to the customer and, in the best case, already know what the customer needs before they call. #PredictiveAnalytics

3. The watering-can principle in sales is inefficient and damaging to business.

This point is not about “reactive sales work”, i.e. a customer calls and wants to order something, but about proactive sales work. That means that sales staff actively approach customers and, for example, offer additional products or sales promotions. Incidentally, price increases are also proactive sales activities. Both fields (reactive and proactive) are part of sales activities.

In this area, sales management with AI is worth its weight in gold. Many sales organizations use such proactive measures in a watering can manner. Possibly, some make differentiation through an ABC analysis. But more often than not, it’s like, “we’ll just shoot as often as we can, and we’ll get some hits.”

Here are a few examples: Price increases on the part of suppliers are passed on to customers one to one; customer loyalty measures are widely distributed, or all customers receive offers on a new product.

How can it be done better? With artificial intelligence. AI-based sales prediction software calculates probabilities for future behaviour of your customers. So: which customer might be most likely to accept which prices? Which customers are most likely to be interested in which products? Or which customers are at high risk of churn?

With these predictions, sales staff can “shoot” much more precisely. The probability of a hit increases enormously. Also, keep in mind that every sales action costs something. By controlling sales with the help of AI, you can achieve more with less.


Sales Management with AI: Why Hyper-Automation in Sales is Becoming Inevitable – Conclusion.

According to Gartner, in the next five years, there will no longer be a separation between sales process, applications, data and analytics, as all four will fall under the concept of “AI for sales.”

The numbers speak for themselves: more and more B2B companies are discovering the value and potential of artificial intelligence in sales. Hyperautomation in sales will be inevitable because, in the long run, no B2B company can afford not to use its data and waste valuable time on manual sales processes.


Further Read (in German language):

Blum, K. (2020): Die Zukunft des Vertriebs im Jahr 2025: Datengesteuerter B2B-Verkauf zur Förderung des digitalen Handels; Hg.: Gartner

Roland Berger (2015): Die digitale Zukunft des B2B-Vertriebs

Märtin, M. (2022): Künstliche Intelligenz im B2B-Vertrieb – Hype oder echter Nutzen?; Hg.:

Deal Code (2022): KI für den Vertrieb: Ausblick auf die Vorteile Künstlicher Intelligenz.