Uncomfortable as it may be to admit, uncertainty lies at the heart of some of the most critical decisions we make in the workplace.
A job applicant may enjoy stellar qualifications and a track record of success, but it’s impossible to know with absolute certainty that her success will be replicated at your organization. There’s no guarantee that major investments — whether they’re in marketing, talent acquisition, new technologies or another company — will yield a high return on investment. New processes and workflows come with their own risks: Will employees adhere to them, and even if they do, will they improve organizational performance?
How do we grapple with the many uncertainties we encounter daily? We assess the totality of the evidence, draw on our own experiences and make educated guesses about the right course of action.
Technology may be one way of clearing the fog of uncertainty, minimizing the risk and maximizing outcomes. Indeed, the proliferation of sophisticated new technologies promises to bring unprecedented intelligence to the decisions we make. Leveraging data-driven insights, predictive analytics, and other applications of computational power, businesses can bring greater precision and accuracy to their most important decisions.
The recent rise of artificial intelligence (AI)-based prediction as a decision making tool is an outgrowth of the growing abundance and availability of data. Today, we’re increasingly relying less on computer logic and more on statistics. Prediction is slowly being taken over by machines as more data becomes available.
What are the practical implementations for today’s businesses? Consider the case of a marketing manager whose company is launching a new product. The marketing department wants to ascertain which of two potential campaigns is more likely to be effective in promoting the product with key target audiences. Campaign effectiveness hinges on several variables, from cost to click rate to expected return. Utilizing a predictive technology platform, such as Optimove or Segment, that marketing manager can see which campaign strategy is most likely to resonate with potential customers, inspire conversions, drive revenue increases and turn a profit. Drawing on heaps of user data, AI technology can help marketers segment their audiences, gain new insights into customer behavior, and optimize their customer relations and marketing initiatives.
The Hiring Process
Not only can AI bring new efficiency and insights to companies’ work, but it can also help select who will be doing the work. While hiring managers possess unique insights into company culture and candidate fit, the often exhaustive task of sifting through dozens or even hundreds of job applications can easily lend itself to human error: a misread application here, an overlooked resume line there, an application reviewed in the wrong frame of mind or wrong time (i.e., a Friday afternoon).
AI software has the capability to read through thousands of resumes and job applications within minutes, a significant boon to hiring managers seeking to winnow down applicant pools and identify the most promising candidates. Drawing on a company’s internal HR databases and defined criteria for the position, AI can match the right candidates to the right opportunities while combating the unconscious biases and limitations of human HR professionals. Startups like Joonko are using AI to attract applicants from underrepresented groups and foster diversity and inclusion in the employee life cycle. Mya Systems is automating sourcing, screening and scheduling through conversational AI, improving the hiring process for both recruiters and candidates.
Health care professionals, too, are turning to AI to make more effective decisions and better judgment calls on a range of issues, from diagnosing diseases to recommending the best wellness plan for individuals and employers.
One of the biggest challenges health care providers face is compiling, analyzing and maintaining vast amounts of medical records, which serve as the basis for making critical decisions about diagnosis and treatments. Tech giants and startups alike are offering solutions that can improve the decision making process and reduce medical errors, which account for the third-leading cause of death in the U.S., according to a John Hopkins study.
The recent launch of Amazon’s new service, Amazon Comprehend Medical, uses text analytics and machine learning to digitize patient records and extract information on diagnoses, treatments, medication and symptoms. A more well-known solution is IBM’s Watson, which delivers data-driven insights that help providers make evidence-based decisions and get a more complete picture of their patients.
According to a CB Insights report, health care AI startups have raised $4.3 billion in the last five years, more than any other industry. One example is Viz.ai, which analyzes CT scans and alerts health care providers of the possibility of a stroke in real time. Beyond Verbal analyzes voice patterns to identify biomarkers associated with neurological disorders, coronary artery disease and other health conditions.
While the applications of AI in the health care industry are showing promising results in augmenting health care decisions, it is important to note that AI is not a replacement for human professionals. The true power of AI can be experienced when human and machine work hand in hand.
The bottom line: AI can help companies make both better decisions and more decisions, bringing scalability to organizations’ most critical processes.
A no-brainer? Not necessarily. While more and more executives are embracing AI’s transformative potential, they have been slow to fully integrate AI solutions into their businesses’ operations. A global McKinsey survey of 3,000 C-level executives found that only 20% currently use AI at scale in their core operations, highlighting the persistent gap between the promise of AI and the reality of its adoption.
Still, the survey underscored that investments in AI technology have sharply increased, with companies investing between $26 billion to $39 billion in AI in 2016. As technological development proceeds apace and early adopters reap the rewards of their investments in research and development, the gulf in performance between AI-savvy companies and the rest will only widen.
One thing is clear: When companies recognize that they can perform tasks more accurately, more efficiently and at scale, integrating AI becomes the intelligent choice.
This article was written by Amir Konigsberg, Co-Founder and President of Twiggle.
Originally published at www.forbes.com on January 15, 2019.