With all of the hype around predictive analytics, it is easy to get the sense that AI and machine learning technology are on the steady warpath towards replacing humans in the workplace. This is a scary thought for many people – particularly for sales professionals. Sales has been one of the main entry points for artificial intelligence into the workplace, and, as a result of this proximity to the tidal wave of predictive technology, sales professionals and sales support professionals are on the front line.
While the idea of AI in the workplace is a scary notion for many, I argue that it will serve as much as a complement to the modern sales professional in 2017, as it will a replacer of jobs in the work place.
The Complex Resistance of B2B
It is inevitable that the steady push of e-commerce technology and AI in 2017 will replace some of the workforce. The most manual of jobs – the order takers, the question answers, etc. – will continue to be replaced.
But what about when the buyer does not know what they want to buy – or does not understand the complexity of their needs? While some replacement is unavoidable, AI technology will not be able to replace many of the key players on a sales team. As the marketplace continues its progress toward solution selling and increased complexity, the value of the “human touch” will become more important in many roles.
This steady push has indeed forced roles to shift, especially in the complex B2B sales world. Sales professionals that are able to evolve their roles from the “seller” to the “trusted advisor” or consultant will remain invaluable. In fact, according to The Death of a B2B Salesman, the consultant archetype has become the model within the B2B world and these jobs are expected to grow by 10 percent by 2020.
The fact of the matter is that the complexity of the B2B marketplace – solution selling, bundles, complex products – will still necessitate human interaction to enlighten the customer and guide them through the sales cycle.
AI Elevating the Human in the B2B Workplace
In a simple B2C e-commerce transaction, AI and machine learning technology can easily provide recommendations for additional products. B2B transactions tend to be bit more complex, however. When a B2B sales person is selling a highly complex product or service, AI technology becomes a secret weapon that allows the seller to be a more agile, sophisticated and trusted advisor to his customer. Insights gained from machine learning allow the B2B sales person to take the conversation to the next level and elevates their role to an effective consultant.
A specific example of this can be seen in the Quote-to-Cash process, which encompasses the quoting, contracting, and revenue management aspects of the sales lifecycle. Machine learning can leverage Quote-to-Cash data available in a CRM (data from past deals) to develop a demographic of the buyer’s company. The technology can then guide the seller through prescriptive recommendations to help provide the right options (prices, products, discounts, etc.) to the buyer.
There are many examples throughout the B2B space of machine learning acting as a tool to the seller, rather than the seller itself. Implementation of such technology will help set businesses apart in 2017 and begin to determine true leaders in the marketplace.
In 2017, AI technology will drastically change the workplace – but the fear that such change will replace the need for people is misplaced. Instead, especially in B2B, where the complexity of products and solutions necessitates a more consultant architype of seller, AI will be more of a cooperative force – one that equips sellers with insights to help drive a higher level of sophistication in sales conversations.
(About the author: Elliott Yama is chief data analyst at Apttus)
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