Every week or so – the news media comes out with a discussion on the future of artificial intelligence (AI). This is followed by much mulling over whether or not it is going to disrupt us in undesirable ways.
Let us consider it a settled issue, as argued in this discussion centering on nurses and librarians, that the purpose of artificial intelligence is to make onerous tasks obsolete, not make us redundant. However, another point of contention is that the introduction of AI systems can turn us into button pushers – we may keep our jobs, but we may come to use it as a crutch and not add unique value like only skilled humans can.
We will show that this concern also carries no weight. The future of artificial intelligence is about coaching – not crutches. In particular, we will be focusing on examples from within the sales discipline since it exemplifies how a people-driven industry can benefit from integrating itself with machine intelligence. It will become apparent that human talent will still run the show – it will simply get a massive boost from having AI on its sideline.
Some people call this artificial intelligence, but the reality is this technology will enhance us. So instead of artificial intelligence, I think we’ll augment our intelligence. Ginni Rometty
Artificial Intelligence and Data Overload
The “IT Age,” if we may use that term for the period following the first dotcom boom, has had a step-wise progression. The first part was defined by expanding the ability of businesses to centrally store enterprise data and creating intuitive software so professionals could make good use of it. The stage that followed this was based on augmenting all of these capabilities with the sharing power of the internet.
The full promise of these periods has been fulfilled. This has left us with software portals optimized for user experience, well-designed and tested data models, and rich troves of information pertaining to our business domains.
Yet with all of this sophistication, we can still easily get bogged down in decision paralysis and endless grinding due to the sheer amount of information involved. The next stage of evolution, therefore, will be defined by our ability to use artificial intelligence as our guiding light through this murky storm.
To give an impression of the sheer scope of data with which we must operate, let us look at this presentation involving sales leaders and executives of several different organizations. We can see that a market segment search for a broad term such as “ERP” can return 45,000 results. A more specific search narrows the possibilities down to 2,500. This is an example that actually uses machine assistance – think of how difficult it could be to sift through markets that large with nothing but human navigation and some mental heuristics.
The artificial intelligence, in this case, does not take over the decision making in terms of who to prospect. Instead, what it does is scale up the scope of the market that a sales team can realistically engage and then helps it zoom in on the prime opportunities.
The Blurring Line Between Leader and Data Analyst
Decision makers in business must now deal with more sources of information than ever before: e.g. social media channels, mobile data, third-party analytics, internal IT systems data, and (increasingly) The Internet of Things (IoT). Managers have broader and deeper sources of insights than ever before, but the catch is that it is no human-scale task creating crystal-clear strategy and action from this constant stream of noise.
According to Forbes, demand for data-driven sales managers is rising. Though you will not need a degree in data science to be a sales manager, you will need an increasing amount of analytic sophistication to synthesize actions from the following channels:
- team performance data as captured by CRM and other sales software,
- the individual pieces of communication used in the sales process (no level of interaction is too fine-grained for this purpose)
- information about individual customers,
- key trends is entire market segments.
The need for human decision makers with rich experience and strong intuition is just as strong as it has ever been. However, our decision-makers will need the power of artificial intelligence to bring their efforts into focus and channel their options into real directives. Think of artificial intelligence in this case as a digital second-in-command.
AI Can Listen
We noted in the previous section that no pieces of information should be ignored as an input to artificial intelligence. We can certainly draw insights from widely available online data and from the behavioral history of those we interact with. At a finer level, we can also use text-based communications and social media content. However, what if artificial intelligence could react to our actual spoken words, providing insight on the fly, creating a holistic view of our efforts, and operate much in the same way that a human coach would?
It turns out that we have reached this point. Thanks to a combination of artificial intelligence, data analytics, and natural language processing (NLP), Chorus can capture sales calls, extract crucial fragments, and orchestrate all of this into powerful guidance for sales teams. This type of activity used to entail a sales manager sitting on calls for a non-trivial amount of time, absorbing many different conversations, and giving feedback that would help mold the team.
Artificial intelligence on the front lines
We have discussed the ability of artificial intelligence to remove much of the work that involves discovery and analysis. However, it is also just as useful to have artificial intelligence act on the “front lines,” automating the manual interaction that burns up much of our time.
According to Engadget, one of the best applications we will see of this principle is in the form of AI-based sales assistants. Having to give each lead an individualized slice of effort eats up resources that can not be efficiently scaled against thousands of potential customers. Using AI to drive initial engagement removes this constraint and can “facilitate engagement with an unlimited number of leads.”
Once again, we should stress that the future of artificial intelligence does not mean that the jobs of sales reps or any other skilled professional are at stake or will simply be put on autopilot. This application of AI allows the rep to have a virtual army that performs the labor-intensive task of making contact and getting the sales process in motion. It is a force multiplier for the human who is then able to focus more on the more personalized tasks of assessing leads and closing.
The Coach Needs Coaching Too
We have made the case for why the future of artificial intelligence is about augmenting our tasks that involve human judgment, not about sitting back and letting a machine handle everything. In fact, it turns out that the machines actually need a little bit of handling from us.
It may be odd to think about giving a computer system feedback, but just like with a real-life partnership or mentorship the interaction goes both ways. Training is the driving principle behind the most effective modern artificial intelligence. Such systems need data from a wide range of sources in order to provide more effective results, and we must keep in mind that only humans can define what training data has value.
One of the best ways to fulfill this is with an integrated data solution such as Tallyfy. Bringing together a range of different sources like CRM, file storage, workflow management, and social media will make it much easier for you to give your artificial intelligence a deep understanding of your operations and how to serve you. We have a greater chance of winning if we allow artificial intelligence to be our coach, but we have to make sure that it has been given the right coaching itself.
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