Skip to main content

The State of AI in Late 2018

Marcelo Andrieu, Technical Product Marketing Manager
October 30, 2018

Artificial intelligence in the business world isn't at all like the far-fetched imaginings of simultaneously fascinated and trepidation-filled science fiction authors of years past. Nor is it the passing fad that some of its detractors or skeptics might have presumed it would be. As with many things, the truth lies somewhere in the middle: AI has a considerable way to go before it becomes part of everyday life the way something like the internet of things is, but it has moved faster in the direction of that goal than even some of its proponents likely thought possible.

Enterprises that remain on the fence as far as adopting AI have a somewhat understandable approach, as the technology still hasn't reached its potential. But such an attitude won't be viable for long. The latest strides made by AI innovators are proof positive of its potential, and could soon be a regular presence in business process management tools. Here, we'll examine a few of the most notable recent developments in the field:

CMU, Oxford collaborate on multiple predictive analytics projects

According to Campus Technology, Carnegie Mellon University and Oxford University both recently partnered with Meltwater, a digital media intelligence firm, on a series of AI projects, many of which revolve around various predictive functions. Predictive analytics are arguably the most valuable form of business intelligence, given their capacity for anticipating eventualities in an organization's foreseeable future and providing a foundation for preemptive mitigating measures.

Oxford researchers and students are specifically focused on improving automation in data science and assessing the accuracy of source documents and news articles. The latter is especially relevant in an era when "fake news" is a near-everyday occurrence rather than an anomaly, and if a business acts based on a rash decision motivated by illegitimate info, the results can be devastating. Preventing this would thus be of great value. Meanwhile, CMU is working on methods for developing AI within cloud computing infrastructure, which could revolutionize enterprises' use of the cloud.

Automation for the future of recruiting

Effective hiringhelps guarantee the success of a company by finding and bringing on the best possible candidates - those who have the potential to be game-changing contributors to the organization's output and bottom line. But the process of combing through resumes can be undoubtedly time-consuming, swallowing up one of the least renewable resources at HR staffers' disposal. As such, Forbes' report on a startup using AI to broaden the reach of hiring managers showcases a development that could have major ramifications in the not-too-distant future.

The company Hiretual developed an eponymous AI-based system that searches for candidates across approximately 700 million professionals' public social media profiles and reviewing more than 30 different job posting and social networking sites. Using custom criteria, the platform finds potential hires for recruiters to review in a quick and efficient manner. Hiretual CEO Steve Jiangexplained his hopes for the company's product over the next few years in a conversation with Forbes.

"In the future, AI will find great candidates for a position before a recruiter even starts a search," Jiangsaid to the news provider. "I believe that HR systems will transform from data-driven to AI-driven in the coming years."

The firm is just getting started, having raised just $1.5 million in operating capital as of Aug. 30, 2018. But it already counts major multi-nationally present businesses among its users, including Amazon, Northrop Grumman and Hilton.

Possibilities of decision-making AI systems

Awareness remains a river that modern-day AI utilities have yet to cross. However, Finland-based firm Sentient Technologies is working on systems for a process it calls evolutionary computation, according to PC Magazine. The initial version of its platform, which debuted in 2014, has already used high-end language processing to aid financial institutions, and will soon move into areas such as genetic research and health care.

In the words of Dr. RiskoMiikkulainen, Sentient's chief technology officer, the company's use of evolutionary computation involves "an algorithmic [approach] motivated by biological systems that allows us to build an AI platform capable of autonomous decision-making." He acknowledged that there's certainly need for further development, but also said the potential benefits a near-sentient AI could offer medicine, agriculture, the energy sector and many other verticals are all but limitless.

Deploying AI through apps

As AI gradually becomes accessible to the majority of enterprises, opportunities will certainly arise to use such technology for customer-facing purposes in retail, media, customer service, health care and other fields. Bringing AI to bear for these needs will optimally involve mobile compatibility, which necessitates apps across multiple channels. Appian's application delivery platform will be ideal for the fast-paced creation of apps that bring the AI experience directly to the client, with low operational costs and agile development capabilities.