Artificial intelligence (AI) is helping companies boost lead volume, close rate, and overall sales performance.
That’s because this technology can automate and augment much of the sales process. As a result, salespeople are free to focus on what matters: revenue.
Forward-thinking companies are catching on to that fact. According to a Salesforce State of Sales report, sales leaders expect their AI adoption to grow faster than any other technology. Salesforce also found that high-performing teams are 4.9X more likely to be using AI than underperforming ones.
Yet AI is not replacing salespeople. The vast majority of companies using AI or planning to also plan to increase staff.
That’s because AI is creating practical value for sales teams by automating, augmenting and supercharging the way they work, with several real-world use cases and tools being used today.
But there’s so much hype around AI that salespeople often miss this fact. We don’t blame them. They’ve got numbers to hit, and too much commentary out there about AI is aspirational, not practical.
In this article, we’ll stick to the practical.
We’ll outline a working definition of AI for salespeople that includes just the bottom line, no fluff or technical jargon.
Then we’ll look at some top AI use cases for salespeople, so you’re armed with some ideas on how the technology can help teams better make their quotas.
Finally, we’ll overview some top companies that use AI to give salespeople superpowers, so you have a few tools to start looking into.
What is artificial intelligence?
Artificial intelligence is an umbrella term that covers several different technologies, like machine learning, computer vision, natural language processing, deep learning, and more.
At their core, though, all of these technologies help machines perform specific cognitive tasks as well as or better than humans.
For instance, AI-powered computer vision systems in self-driving cars are able to identify obstacles just like people do, allowing the machine to take the wheel.
Your favorite voice assistant, like Alexa or Siri, understands your words just like another person, then responds in kind—all using AI.
Amazon and Netflix use AI recommendation engines to offer up products and movies you might like, making assumptions about your preferences just like a fellow product or movie enthusiast might.
While there are a ton of complexities to different types of AI, all you really need to know right now is that “artificial intelligence” describes many different types of smart technologies. And many of these technologies can impact your sales career and performance in profound ways.
That’s because AI isn’t just automation, though it may include elements of intelligent automation. AI takes things a few steps further. These technologies analyze large datasets. They don’t just crunch numbers, though. They use advanced computer science techniques and superior computational firepower to extract insights from data. These insights can then be used to make predictions, recommendations, and decisions.
This type of AI, "machine learning," powers the most impressive capabilities in sales. Machine learning is a type of AI that identifies patterns based on large sets of data. The machine uses these patterns to make predictions. Then, it uses more and more data to improve those predictions over time.
Technology powered by machine learning gets better over time, often without human involvement.
This is very different from traditional software.
A typical non-AI system, like your accounting software, relies on human inputs to work. The system is hard-coded with rules by people. Then, it follows those rules exactly to help you do your taxes. The system only improves if human programmers improve it.
But machine learning tools can improve on their own. This improvement comes from a machine assessing its own performance and new data.
For instance, a marketing AI tool exists that writes email subject lines for you. Humans train the tool's machine learning using samples of a company's marketing copy. But then the tool drafts its own email subject lines. Split-testing occurs, then the machine learns on its own what to improve based on the results. Over time, the machine gets better and better with little human involvement. This unlocks possibly unlimited performance potential.
Now, imagine this power applied to any piece of marketing or sales technology that uses data. AI can actually make everything, from ads to analytics to content, more intelligent.
This means sophisticated AI can analyze customer and prospect data, predict which prospects are most likely to close, recommend the most important sales actions to take, forecast results, optimize pricing, and much, much more.
Thanks to this power to augment and improve sales performance, McKinsey analysts writing in Harvard Business Review estimate that AI can create $1.4 to $2.6 trillion of value in marketing and sales.
How can machine learning increase sales?
So how can the power of machine learning help you sell more? Check out the top use cases for the technology below.
Artificial intelligence systems exist that can predict or forecast outcomes using historical data to inform future results. Common predictions that sales AI systems can make include:
Deals or prospects most likely to close.
Deals or prospects to target next.
New customers that may be interested in what you’re selling.
Now, the accuracy of those predictions depends on the system being used and the quality of the data. But the fact is that, with the right inputs in the past and present, AI is capable of showing you who is most likely to buy in the future.
Predictive forecasting can also create value for sales teams internally.
Using the same types of data analysis, AI can help sales managers forecast their team’s performance for the quarter well in advance, so they can take proactive steps based on the numbers.
Lead scoring and prioritization
Artificial intelligence can look dispassionately at large datasets from a number of sources and tell you which leads you should prioritize, based on the scores the AI has given them.
As noted by sales pro Victor Antonio in Harvard Business Review, human salespeople usually approach lead scoring and prioritization in an unscientific way:
“Often, this decision-making process is based on gut instinct and incomplete information. With AI, the algorithm can compile historical information about a client, along with social media postings and the salesperson’s customer interaction history (e.g., emails sent, voicemails left, text messages sent, etc.) and rank the opportunities or leads in the pipeline according to their chances of closing successfully.”
In this case, AI can bring a level of logic and standardization to the process that humans just can’t match.
Beyond prediction and prioritization, some AI systems may actually recommend sales actions, going so far as to tell sales teams which actions the system thinks make the most sense, based on your goals and insights from the data.
These recommendations may include advice on how to price a deal, who to target next, or which customers to target first with upsells or cross-sells.
The result is targeted guidance on what actions to take, so salespeople can free up bandwidth to close deals, rather than deliberating about what to do next.
Performance and productivity enhancement
AI can also automate or augment your work to take away some of the drudgery that distracts you from higher-value tasks.
AI can help with everything from managing your calendar to scheduling meetings to assessing a sales team’s pipeline by automatically doing these things for you or making them dramatically easier by using your historical usage data to make decisions. This use case is very similar to how some consumer calendar and productivity apps work, recommending recurring events or to-dos dynamically thanks to AI.
Vendors that offer AI tools for sales
Now that you know what AI can do, you might be wondering what solutions out there actually do it. There are plenty of quality vendors in the space that serve sales organizations of various sizes.
One of the top players in AI for sales is (not unexpectedly) Salesforce. The company’s AI is called “Einstein,” and it shows up in many places throughout Salesforce’s Customer Success Platform.
Einstein automatically prioritizes leads for your sales reps. It evaluates the likelihood of deals to close. And it empowers developers to bake AI into their Salesforce apps.
Salesforce Einstein is a prime example of how many players in the AI for sales space are existing companies. Big existing players, at least the savvy ones, are incorporating AI into existing platforms by hiring AI talent or buying AI companies.
Drift helps businesses use conversations to remove friction from their buying process with chat, email, video, and automation products. These products, powered by machine learning, work together to qualify leads 24/7—essentially cloning your top sales reps.
Conversica is another major player in the space, with $87 million in funding. The company provides an automated AI sales assistant that engages your leads in conversation. The AI assistant conducts conversations with leads, further qualifying them before they talk to a rep.
This type of intelligent automation provides a number of benefits. Human reps are freed up to actually sell to people who are interested in a product or service, rather than wasting a lot of time talking to people who aren’t qualified. Every lead gets a follow-up, since the AI assistant can scale easily.
It’s a perfect example of how machine and humans can collaborate in sales to unlock even more value.
Exceed.ai uses AI to engage with every sales lead that enters your pipeline, using human-like, two-way conversations by email and chat.
Crayon's AI-powered competitive intelligence tool tracks 100+ data types across hundreds of millions of sources to tell you exactly what competitors are up to online. This information is then used to automatically build and update sales battlecards that get results.
AI sales enablement
Now that you understand what's possible, how do you actually get started with AI and machine learning for sales? To use AI for sales enablement, you need to start by taking a few proactive steps.
1. Understand the basics.
You don’t need to be a technical expert or a programmer to take advantage of AI tools. But you do need a basic foundation in AI's key technologies and terms. This post will give you a head start.
2. Learn more about the critical skills you need moving forward.
By partnering with AI-powered tools, today’s salespeople can delegate their administrative work and return to their original skill set. The ability to build relationships, listen actively, and make people comfortable have regained priority. This post breaks down the skills you need to prioritize in your career moving forward.
3. Experiment with the technology.
Many AI tools are available to experiment with. Hands-on experience is a must, since tools and their capabilities vary. Plenty of companies offer free trials or demos of their tech. Start exploring AI-powered vendors in sales. You can click through to any of the vendors we mentioned above—or see our deep-dive profiles below on top AI sales vendors.
- Drift: How to Clone Your Best Sales Reps with AI
4. Get started now.
If you're a salesperson, sales manager, or a marketing professional who works on sales enablement, AI can help you increase revenue and reduce costs.
That means now is the time to get started with AI, no matter your skill or comfort level.
To do so means you build a potentially insurmountable competitive advantage. To delay means you risk getting left behind.
Good news, though:
You can accelerate AI adoption in your career and your company by accessing our free Ultimate Beginner's Guide to AI in Marketing.
The Ultimate Beginner’s Guide to AI in Marketing is a free resource with 100+ articles, videos, courses, books, vendors, use cases, and events to dramatically accelerate your marketing AI education. It's based on the years we spent on research and experimentation—and you can access this knowledge in a fraction of the time.
About Mike Kaput
Mike Kaput is the Director of Marketing AI Institute and a senior consultant at PR 20/20. He writes and speaks about how marketers can understand, adopt, and pilot artificial intelligence to increase revenue and reduce costs. Full bio.