Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

Will Business Development Ever be Automated?

saratogainvestmentcorpAutomation is already here.

At times, it feels as if we’re in a real-life version of the parable of the frog and the boiling water: automation has encroached on our society so subtly and carefully that by the time we’ve realized the consequences, it’s too late. Despite the fever pitch of the anger around outsourcing jobs to foreign nations, the fact of the matter is that automation is far more devastating to human labor, especially in the long-term.

But what about business development? Will BD fall to the influx of computers and machines like factories and stock traders? Or should we expect a more optimistic future?

Read More: Interview with Ben Goertzel, CEO at SingularityNET

Which jobs will fall first?

Every day, it seems that more and more industries, companies, and workers are falling to automation. Indeed, a 2017 report by the McKinsey Global Institute found that up to 800 million global workers could lose their jobs by 2030, replaced by robots. Much of this upheaval will come in richer nations, like Germany and the United States, where up to one-third of the workforce may have to retrain for new roles.

On the other hand, the finer details of the upcoming job disruption are far more difficult to predict, particularly when it comes to determining which jobs will be replaced. Still, there are some general guidelines we can follow. An earlier McKinsey study in 2016 laid out some interesting criteria: basically, those jobs least likely to be replaced by robots deal with highly unpredictable work, which often involves lots of creativity, management, and the application of long-term, hard-won expertise (though this last factor is being threatened by ever-more powerful machine learning).

However, the most easily automated jobs (automatable?) are those which are highly predictable, and can most easily be programmed into a sequence of steps and functions easily executed by “dumb” robots. For example, office staff and administrative assistants, which commonly handle routine duties such as data input, transcription, and scheduling, have a 97.6 percent chance of being automated. On average, such jobs don’t require clever solutions, negotiation, squeezing into small spaces, or personally helping others.

In fact, based on these principles, the BBC created a handy tool which determines the likelihood that certain jobs will be automated. For instance, authors, writers, and translators have a 33 percent chance of automation, whereas farmers have a x76 percent chance of automation (fairly likely). Business development and sales managers, however, only have a 16 percent chance of automation–good news for our industry indeed.

Read More: The AI Gold Rush: How to Make Money off AI and Machine Learning!

But why?

The nature of BD

Related Posts
1 of 496

When it comes to automatability, a good rule of thumb is this: does your job rely on competencies where computers are weak (but people are strong)?

For business development, the answer is a resounding yes, and if you’re not convinced, then take a look at the nature of our profession. As a BD professional, we spend most of our time in those exact areas which machines are weak: negotiation, clever solutions, and personally helping others (the tight spaces rule varies by office).

Think of it this way: machines may have passed the Turing test (fooling people into thinking that a hidden computer is actually a human), but fooling individual respondents is a far cry from the complicated interactions between people–especially between BD pros and businesses. For example, an entrepreneur looking to scale up a promising business from a small, family-owned shop into a larger corporation won’t necessarily trust a computer to do so. They need someone with the right connections, experience, and skill to help their organization grow.

This is the heart of the BD automation dilemma: thus far, managing people, improvising creatively, and creating and executing business strategy all require a level of social intelligence that computers don’t yet have. True, algorithms are rapidly improving their lateral thinking, even managing to beat masters of the notoriously abstract game of Go; but however creative a computer may be, empathy is an entirely different story.

In fact, if recent developments are anything to go by, empathy (along with human-like traits like ethics and morals) may be impossible for machines to fully grasp. True, computers can learn to read our emotions; but there’s a world of difference between reading human emotions (and responding in a preset way), as opposed to understanding emotions deeply and empathizing with your subject. The latter is what is required, especially if you want to close deals and enter a sustainable, long-term partnership with your BD client.

Read More:  Fluor Uses IBM Watson to Deliver Predictive Analytics Capability for Megaprojects

What is the future of BD?

Now that we’re settled in the security of our jobs, another question comes to mind: what will BD look like in this brave new world of automation? Though it’s hard to say with any certainty, we can extrapolate.

For one, expect partnerships between humans and computers–something that is already happening. Under this model, known as augmented intelligence, algorithms would take away the majority of the mundane work, leaving humans to focus on the higher-level tasks and duties–and aiding them in the process. Lawyers, for instance, use document discovery software to rapidly analyze thousands, or even millions, of pages in order to discover actionable legal insights. In much the same way, BD pros could use computers to parse contact lists, running them through filters to find the most promising leads and automatically generating profiles (and perhaps even scripts).

Augmented intelligences could also help coach human employees in best practices. The key advantage of this networked software is that they have plenty of data points to work with–and unlike their flesh-and-blood partners, don’t have to rest. Therefore, a program could conceivably serve as a real-time, on-the-job coach, helping employees through difficult tasks and then feeding data back into the system. In terms of BD, this could lead to an algorithm coaching an associate through outreach to a new and unfamiliar industry, such as the chemical industry, helping them learn buzzwords and important concepts, and guiding them through each step of the interaction.

In business development, at least, it’s hard to see how algorithms can completely replace humans. Certainly, some disruption is to be expected, perhaps in entry-level positions such as analysts. All the same, the core of BD work is remarkably resilient, at least where it concerns automation: because we deal so heavily in negotiation, creative problem solving, improvisation, and empathy, it’s difficult (if not impossible) for us to be rendered completely obsolete.

Read More: The Top 5 “Recipes” That Give AI Projects a Higher Likelihood of Success

Leave A Reply

Your email address will not be published.