Are robots coming for our jobs? Media channels on all sides seem to want us to think so, and yet every wave of technology revolution leaves substantial jobs still on the market. The thing is, creating artificial intelligence that is as fully capable as a human requires the so-far-impossible task of designing a complete human replacement. Instead, each wave of AI development improves the work we already do, allowing us to accomplish faster and more accurate work.
No calculator ever replaced a mathematician. But advanced computers allowed mathematicians to avoid the tedium of rote calculation and focus on formulating the theorems that drive mathematical research. In the same way, developments in AI have assisted professionals in numerous fields or created new and more agile markets. We might have replaced a couple of sales representatives with an Amazon Echo on the coffee table enabling the automated placement of orders, but the net gain to business creates jobs too.
- Case study: Evisort
The legal profession is swamped with the bottleneck of contract management. Any given contract might be 30 pages long, a given workweek might assign 20 contracts to review, and all of this has to be done not by a firm, but the legal department at the average company.
Evisort created a legal knowledge engine for managing contracts. It uses deep learning AI to fetch key data points from contracts, retrieving metrics like dollar amounts, dates, named parties, and countless clauses that it can sort and catalog into easy-to-digest reports, cutting months of research time down to seconds.
Evisort, founded in 2016, has already pulled in $5 million in seed funding and attracted clients from the Fortune 500 down to Silicon Valley startups. Not only has Evisort transformed legal departments into faster, leaner teams, but it is capable of helping companies avoid undue expenses or take advantage of new opportunities by helping a company stay on top of its legal obligations and other parties’ obligations to them. Lawyers, on learning that Evisort can jam through a contract in seconds, lament the fact that they’ve spent a decade of their lives doing this the hard way.
Here are a few other ways modern AI developments have cut company expenses:
- Deep 6
In the field of medical research, every time a clinical trial is undertaken, the researchers must first discover a new batch of test patients. The problem with testing, say, a new cancer drug is that you have to round up a number of patients with that particular kind of cancer. Deep 6 automated this search by matching patient medical record charts against a set of criteria, cutting research time down from months to minutes. Like many of the companies on this list, Deep 6 uses deep learning AI to parse medical jargon, contextually making matches for certain conditions and diagnoses.
On a common thread with the rest of these innovations, once again the problem is researching through paperwork. In this case, it’s scientific research papers, the results of which require highly specialized knowledge systems to comprehend and sort through. Again reducing a company’s research effort from weeks to minutes, Algorithmia can help business develop new products and methods based on a faster, more comprehensive research overview.
Marketing departments have a problem with big data management too. The issue here is analyzing the volume of customer data into a comprehensive report that can help target individuals with sales pitches more likely to work. Salesforce has an AI, fittingly named “Einstein,” which helps sales teams better understand their marketing focus and target customer base. Teams who use Salesforce soon find conversion rates going up by as much as 10%, proving that even sales professionals can use some artificial assistance.
AI is a powerful tool, and companies that use it wisely will find themselves with a competitive edge over late adopters. Like other technology innovations, it has its place and time and will prove to reshape the business landscape.
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