AI Revolutionizing Sales: How Artificial Intelligence is Transforming the Selling Process

Sales processes have lagged behind digital tech for years, especially in finance and logistics. Now, however, with AI rapidly reshaping many businesses, the sales industry is at the forefront of adopting generative AI in its routine operations.

And while AI tech has not yet become a digital assistant for every salesperson out there, the industry is already on the way to large-scale AI automation.

No wonder a typical sales manager’s responsibilities include working with high amounts of largely unstructured data — something generative AI excels at. On the other hand, there are still a few challenges to overcome before generative AI becomes common in every salesperson’s toolkit.

So, let’s take a quick look at which companies already use AI to enhance their selling operations, how exactly they do it, and what we can expect from AI’s steady expansion in the sales world.

Artificial Intelligence is Transforming the Selling Process

What AI Already Accomplishes in Sales?

Even though AI is still in its early stages, it already streamlines plenty of routine sales operations, primarily dealing with analysis. More specifically, AI is already great at:

Alleviating Administrative Workload

Selling is not just about creating catchy pitches — for the most part, it is still about reporting. The larger the corporation, the more paperwork — especially in international businesses that have to deal with legal compliance regulations and a series of obligatory approvals before the next step is to be taken.

Besides, many SaaS marketing tools, including world-known providers like HubSpot, Soho CRM, and SalesForce, have been using AI reporting capabilities for years. As a result, sales managers have more time for creative tasks.

Amplifying Customer Interactions

AI has significantly alleviated email and other written forms of communication with leads and customers. The most obvious example is the mass use of email writing assistants, like Grammarly Business or Crystal Knows, to enhance direct communication.

Still, there are more advanced text analyzing capabilities that can pick up subtle hues in writing and prompt sales managers to phrase a correct response, increasing the chances of successful conversion.

Today’s generative AI is also good at giving sales managers suggestions on which leads in the corporate sales funnel have the highest chances of converting, as well as offering tips on the best strategies to accelerate this process.

AI integration into sales pipelines offers a chance to boost sales because managers spend less time analyzing lead behavior (both horizontally and vertically) to come up with optimized suggestions.

Automating interaction with the customers is another task that falls under the same category. No one is surprised today when they get a marketing email addressing the recipient by name, but modern AI tech is taking this to a new level.

Not only does AI successfully automate the email flow, but it also helps segment leads according to the different stages of their buying readiness.

Based on this data, promotional materials are sent depending on how far the lead has gone down the purchase ‘rabbit hole.’ So, next time you get an email that offers you to buy something you are ready to buy just now, you can be certain that generative AI is behind it.

Analyzing Consumer Preferences

Another area in which generative AI already excels is giving customers personalized suggestions on the products they might enjoy.

Sales giants, including Amazon, Apple, Spotify, and Netflix, use generative AI’s predictive capabilities to offer their subscribers tips on what they should watch, read, or listen to next.

Such functionality is no surprise in the digital sphere, of course. But it is also spreading into the tangible world. Coca-Cola has been experimenting with AI-driven vending machines for a while now and has already achieved impressive results.

The analysis of customer preferences is later used to determine which flavors make the most profit, guiding the company further with its flavor experiments.

However, it also has impressive capabilities for users, offering them the ability to experiment with the available flavors right on the spot, so it is a win-win for both parties involved.

Sales Intelligence and Predictive Analysis

This is another generative AI area that borders on reporting and pattern analysis, but it takes the insights a little further.

Machine-learning algorithms collect data, arrange it into recognizable patterns, and come up with predictive suggestions for increasing sales and driving conversions.

Technically, the logic behind this functionality is the same as with scoring leads and offering suggestions on how to engage them for a quick conversion.

However, with advanced sales intelligence and prediction tools, AI tests and validates larger amounts of data. Sophisticated business solutions, primarily designed for the B2B segment, can formulate attainable long-term strategic goals, segment marketing steps according to different locations and demographics, discover new promotional opportunities (if not entire market gaps), and much more.

Notably, these are only the early days of generative AI, but the capabilities in sales are already impressive. On the other hand, some limitations still exist — so let’s take a look at those, too.

Obstacles to Overcome in the Future

In general, AI’s expansion in the world of sales is hindered by a lack of human talent with a deep understanding of both AI algorithms and the selling process. This is not surprising because the technology is still relatively new.

Currently, there are several areas that need improvement, and, considering the pace at which the tech is going, we expect to see new developments soon enough. Especially when it comes to:

Increasing Accuracy and Consistency

Even though AI accuracy has gone a long way in a few short years, there is still plenty of room for improvement.

Anyone who has toyed with ChatGPT knows that the same question can sometimes prompt very different answers. In the machine-learning context, businesses that regularly fine-tune AI algorithms to their own corporate data have a clear competitive advantage.

On the other hand, not every sales business has the budget and resources to keep ‘educating’ their AI assistants.

Accelerating AI Integration Processes

As already mentioned, algorithms to improve data accuracy today rely on gradual machine learning, but with the advance of learning algorithms, companies may expect quicker integration into their internal systems.

So far, one of the weakest areas in sales is estimating the value of a given geo market or offer. And, few AI systems can properly analyze customer feedback and testimonials to include these data in predictive analyses.

It’s all about trial and effort right now, but advanced machine learning algorithms can eventually lead to quicker AI integration.

Balancing Functionality and Cost

This is a common challenge for any new tech and, without any doubt, one of the major obstacles in AI expansion. So far, only large businesses have the resources to regularly fine-tune their internal AI capabilities. In contrast to that, small companies still rely on human talent for many routine tasks.

Takeaway: Will AI Replace Salespeople?

The scenario in which machines take over all of the human tasks is still unrealistically far. On the other hand, generative AI has already become an indispensable assistant for many salespeople, and its expansion in the marketing world will continue.

However, the current situation requires new human talent with a deep understanding of marketing and AI tech before new developments are possible. It is clear that AI will soon take over most of the routine sales tasks.

At the same time, it will give sales managers an opportunity to focus on narrowly specialized needs that require human creativity.

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