Last year, my company, HRExaminer, published the first comprehensive analysis of AI in HR. At the time the research began in May 2017, there were about 40 companies claiming to use AI in HR. By the time we were finished, in October 2017, there were 65. At year’s end, there were more than 100.
Today, the number is close to 200. That’s a 500-percent year-over-year growth, and it’s going to accelerate. Every piece of software used in an enterprise setting will have some element of intelligent software: prediction, forecast, recommendation, decision filtration, data consolidation or sentiment analysis. In the long haul, it probably won’t be called AI.
When I ask audiences of HR executives who is buried in solicitations for AI services, all of the hands in the room go up; yet, when I ask if they understand the differences among vendors, no hands go up.
Buyers and decision-makers are swamped with competing, hard-to-validate assertions. The urgency and certainty with which they are delivered belie the unproven nature of most of the hype. To quote Bob Dylan, “Something is happening here, but you don’t know what it is.”
The assertions are pretty hard to distinguish from one another—as many vendors say they’re the first or the only using a certain technology, pledge to eliminate bias or help companies learn what their employees are really thinking. Almost all claim an improvement in process efficiency, and uniformly compare human- and machine-error rates. However, AI services are more expensive to install and operate than they appear.
Most of the vendors in the market today cleverly use statistics. Since the cost of processing and storage is now negligible, software can run endless calculations for free. Today’s AI vendors sell subsets of what will become AI. It works because you can inexpensively run complicated statistical algorithms, but it’s not really AI—it’s a step along the path to AI.
The Second Annual Index of Intelligent Software in HR will publish this summer. In the evaluation, we are building a representative sample of the best that the market has to offer, including vendors’ claims, the realities and the critical factors companies should consider when purchasing software. The report builds on the technical tutorials offered in the first edition.
The idea is to create a framework for evaluation while illuminating the technical, legal and ethical risks associated with implementation and product use. As a favorite talent-management leader once said, “Really well-defined HR and recruiting processes are the foundations of … class-action suits.” In other words, the efficiencies that can come with process automation go hand in hand with unintended consequences.
As is the case in all other technical revolutions, the bulk of competitive value accrues at companies that take the risk of adopting early. The arena is fraught, and the opportunities to establish a sustainable competitive advantage in HR practices are enormous.
Focusing the Conversation
The HR Technology Conference & Exposition® in September will include a set of curated sessions that cover the fundamentals of, and bright spots on, the AI landscape, as well as ethical issues and purchasing guidelines.
Here’s a synopsis of those sessions:
Conference Orientation—This is the third year for the well-received orientation program. You can catch it the day before the full conference begins, in the time slot immediately following the amazing Women in HR Technology Summit. Part technology tutorial and part insider’s view of what not to miss, the session gives participants a chance to organize and focus their conference experience. As was the case in years past, the orientation offers recommendations on must-see AI vendors and must-attend sessions, as well as a framework for thinking about the various vendors. There will also be webinar versions of the orientation in advance of the conference.
AI Fundamentals—This session covers three areas: technology basics, major ethical questions and results of the Second Annual Index of Intelligent Software in HR. It is an introduction to both the technology and the market. If you’re looking to get a running start in AI (or a quick look at the state-of-the-art tech), this is where to begin. Expect a simplified view of the underlying technologies, a deep look at the shape of the market and a grounding in the most important ethical issues. The session will investigate the question of whether AI techniques that are useful for managing things should also be applied to managing people.
Questions to Ask When Evaluating HR AI Products—This will be a conversation with a single customer about the questions asked during the initial purchase of intelligent software. At the heart of this conversation is the need to cut through the noise, evaluate security issues, understand the total cost of ownership and explore the quality of data sources. A big part of the value delivered by AI systems depends on the vendor’s data model and sources. The discussion will revolve around comparing and contrasting different approaches.
HR Tech AI Best-in-Class Showcase—Four companies, picked as the result of HRExaminer market research, will deliver disciplined, well-oiled, seven-minute presentations about their business models, intelligent services, implementation processes, data models and customer support. The companies represent how emerging industry leaders can solve different aspects of the HR-tech problem set.
Is Tech Eliminating or Amplifying Bias?—Heather Bussing of HRExaminer and Kate Bischoff of tHRiveLaw and Consulting are the two brightest legal minds on the topic of technology and bias in the workplace. They are also steeped in technical expertise. In this conversation, they will illuminate approaches that effectively address workplace bias and those that don’t. Many AI vendors claim to be able to eliminate bias, but Bussing and Bischoff will help the audience see the risk in that approach, how to mitigate it and how to define your company’s needs when purchasing AI technologies.
At HR Tech, you can expect to be deluged with multiple (often conflicting) points of view about what AI is and how to harness it. These five sessions are intended to give you ways to think about the issues, an understanding of the research and a look at the best the industry has to offer.
Surveying the Landscape
Expect the topics of AI, analytics, predictive tools and data to dominate the discussion and the vendor exhibit hall at the conference. Here are some of the themes you will encounter:
Performance Management—Although there is a growing sense that performance-management systems cannot simply be jettisoned, their utility remains a vibrant topic of conversation. The offerings in this category include machine-assisted coaching of supervisors to help them develop a team; deep interaction among employee-development, learning-content and performance-management systems; hyper-scheduled check-ins coupled with pulse surveys; and employee-sentiment analysis.
There is a clear connection among engagement scores, company morale and performance management. Several of the vendors use AI to blur those distinctions in the pursuit of performance improvement for the overall organization.
Candidate-Experience Improvements—Recent advances in recruiting technology have included an increased emphasis on the quality of a candidate’s interaction with a prospective employer. Many of the same variables apply to questions of internal mobility. There are several solutions coming to the market that use statistical techniques to help external and internal candidates navigate their careers and the job-hunting process. Offerings include programmatic control of advertising for budget and quality; website-experience personalization for candidates; career discovery that shows the historical linkages among specific jobs; and skills analysis that allows recruiters to understand job requirements more broadly and helps candidates see additional opportunities.
Recruitment Optimization—There are layers upon layers of inefficiency in recruiting processes. Solutions in this category range from comprehensive toolkits as part of an overall recruiting platform to individual point solutions. There is a resurgence of emphasis on matching because of the improvements gained from natural-language processing. Multiple vendors promise to predict the likelihood that a candidate will be open to new job opportunities, and there are a few integrated interview-scheduling tools that should save lots of time and money. Candidate-discovery tools help users sift through massive amounts of information.
Changing Business Models—The explosion in AI tools is driven by a radical increase in the numbers of things we measure and the data we gain from those measurements. Old views of what belongs in which HR silo under which circumstances are under assault. Crowd-sourced labor markets with a single invoice are being delivered in a variety of forms. Training can now be purchased as a Netflix-style subscription, and it’s now possible to buy tools that will illuminate the real organization (not the one in the organizational chart). There is even a company that will predict (with accuracy) the likelihood that a given team will meet its objectives.
Suite Providers—There are 12 to 15 major HR Tech suite providers making the case that their way of integrating data is superior in the aggregate to any single-point solution. Each of the “usual suspects” brings a unique point of view to the arena. For instance, Cornerstone focuses on learning first while Ultimate Software builds employee-sentiment analysis into the core of its offering. Workday is focused on data integration and planning at its core, while Ceridian’s efforts flow from its workforce data, and Kronos uses historical data to make schedule recommendations that are tied to KPIs.
The Disruption of HR Itself—If you look carefully, you’ll see products and services that bypass traditional ways of thinking: performance-management tools that act like learning-management systems; scheduling tools that become full-scale workforce-planning tools and others that improve the supervisor’s plan; and behavioral analytics that allow operations professionals to make better decisions.
And that’s just for starters.
The advent of intelligent software also creates an array of ethical issues. As machines take a greater role in understanding and managing people, there will be a constant clarification of the different roles people and computers play. Expect to see some unintended consequences while we explore the difference between a recommendation and a decision. The difference, of course, is that a decision involves liability, and a recommendation doesn’t. The underlying question as to when a recommendation becomes a decision will occupy lots of conversation in the coming years.
This year’s HR Tech Conference promises to be a gateway for learning about the future of the profession. As sci-fi author Bruce Sterling says, “The future is already here. It’s just not evenly distributed.” You can get to see the future firsthand at this conference.