What if your workforce could be freed from repetitive tasks that are simple, but can lead to errors if an employee is tired? How many other more important tasks could that employee focus on? That’s just part of the promise of artificial intelligence (AI) in the workforce. The technology may even be able to make better decision-makers of your employees, taking the emotion and bias out of the calculation of risks and benefits.
The technology is still in its infancy as an implemented workforce management tool, so Training got input from experts in the field, some of whom work for companies that have developed AI systems, to shed light on how it can best be used and the role it can play in training.
A Higher Level of Accuracy and Efficiency—With Training
It isn’t that your employees can’t do the work, but that an AI system might be so much better and faster at it. One such system is Chooch, a visual AI solution, that includes an application programming interface, a dashboard, and a mobile software development kit. Combining computer vision training with machine learning, the platform offers autonomous labeling, data collection, and neural network selection, among other functions. Its developers say the technology has real-time facial and object recognition applications in the media, advertising, banking, medical, and security industries. But as impressive as the technology sounds, human trainers still will be needed.
“Machine learning [systems] in particular are going to be great decision-support tools for analysts and others who need to sift through thousands or millions of data points to make decisions,” says Emrah Gultekin, CEO and co-founder of Chooch. “Ultimately, these systems need to be trained similarly to how you train humans, so there is going to be increasing demand for people who are experts in their specific fields. These trainers will train AIs. We do exactly this for visual AI. We take an expert’s visual capability and clone it into an enterprise or consumer-facing system.”
In the trucking industry, for example, AI can help drivers be both more efficient and safer, says John Kearney, CEO of Advanced Training Systems, a high-tech simulator technology and engineering firm. “AI has the capability to handle more tiresome and burdensome tasks that require precision without much thought,” he explains. “Also, AI sensors can help monitor both vehicle and driver behavior, including when to speed up or slow down, optimizing fuel consumption and reducing maintenance costs. This holds a lot of promise for the future because it can enhance the productivity of jobs, not just eliminate them. If we continue to see the advancement of AI, it will give the next generation of truckers the assistance they need when driving on U.S. roadways.”
As “intelligent” as this AI is, human trainers still will play an important role. “Overall, AI can create $400 billion to $500 billion in value for transport and logistics alone, which presents a lot of opportunity to integrate new technology for future truckers. However, part of the training process with simulator training often involves human instruction,” says Kearney. “When truckers are not properly trained in simulators that use AI to accurately prepare for adverse events such as snow, ice, or rain, they will encounter situations in the real world they are not trained for, or are trained negatively for, and cause accidents. Thus, AI will be instrumental in pushing the envelope for advanced driver training, which the industry needs, along with human interaction, as a must for new drivers.”
Trainer’s Best Friend
Just as trainers will need to train AI systems, AI will be a help to trainers, facilitating learning. A technology that is already doing this for trainers is VoiceVibes, a startup that uses AI to help people improve their oral communication skills. The company’s automated coaching tool helps people sound more natural and polished when they speak, so they can transform how others perceive them. Used by organizations for communications coaching, sales readiness, presentation skills practice, patient experience training, and interviewing, its creators say VoiceVibes is the only platform with automated feedback to tell speakers how others are likely to perceive them—across 20 areas called “vibes.”
“AI is used to analyze features and patterns in a person’s speech and predict how a typical audience would perceive them. By providing objective, honest feedback, the software helps speakers increase self-awareness, and coaches them to adopt a more effective communication style,” says Debra Cancro, CEO and founder of VoiceVibes. “For example, it shows exactly where in your speech you were most boring or detached, as well as where you were most captivating or authentic. Hearing your own behaviors and seeing examples of ‘good’ and ‘bad’ is an effective way to help achieve your personal best.”
Cancro says the VoiceVibes technology already is supporting training and development in universities, sales teams, call centers, and health care. One company that is benefitting from this technology is collections firm Access Receivables. “Coaching on live calls is dangerous and too late,” says Access Receivables President Tom Gillespie. “In some cases, a misunderstanding in tone can lead to a lawsuit or a complaint. It needs to be practiced before the rep gets on the phone, and practiced consistently.”
Gillespie says VoiceVibes takes the guesswork and the subjectivity out of this training. “For example, reps might feel they are compliant when they greet the customer with the right script, but, in fact, they are coming across as disinterested,” he explains. “Using VoiceVibes helps reps to get better results because it teaches them how to say what they are saying. It improves results.”
Trainers also may find that AI helps them achieve the ultimate goal of learning—to create more productive employees who have time freed up to concentrate on the most important tasks. In addition, graduates and Millennials have grown up with such AI-based tools, so any company that does not embrace the technology will not be perceived as an attractive employment prospect, says Paul Bagley, chief learning officer for Unify. “Moreover, in thinking of the bottom line, not only would other companies likely have a competitive advantage and a lower cost base, they also would have a greater degree of individual productivity [using AI]. The routine, boring tasks can be automated, and routine old-fashioned, time-consuming, page-turning e-learning would be superseded by adaptive learning, which can save approximately 30 percent of the learner’s time.”
In addition, AI can be used to identify where more training is needed, and then to measure the results of the instruction, says JD Dillon, chief learning architect at Axonify and founder of LearnGeek. “More progressive organizations are starting to apply AI to identify knowledge/skill gaps and measure the impact of training on their business results. For example, Axonify clients leverage the platform’s Impact capability to determine how digital training is impacting business results and make proactive adjustments to their learning strategies,” he says.
AI also can ease employees’ days by answering often-asked questions. A technology called Spoke, for instance, offers an AI-powered help desk that answers repetitive employee questions about payroll, benefits, policies, and IT issues, freeing up internal support teams (such as IT, HR, and Operations) to focus on essential tasks, says Spoke Co-Founder and CEO Jay Srinivasan.
Encouraging Employee Self-Direction
Trainers also may find they can support more individuals by leveraging technology, say Camden Consulting Group Senior Partner/Managing Director Margarete Dupere and Partner David Brendel, MD, Ph.D. “New technologies are poised to lower coaching and training expense, increase its accessibility, and enhance the client’s self-directed learning experience. While some surely will continue to benefit from human coaches and live in-person training, many will have the option of supplementing or even replacing coaching and learning with apps, chatbots, avatars, electronic games, and a host of other technologies,” Brendel says.
As important as workforce trainers always will be, Dupere notes that AI boosts a company’s ability to create self-directed employees. “Employees reap significant benefits of live interactions in executive coaching, manager and peer feedback, facilitated training, mentoring, and teaming,” she says. “At the same time, so much of the success of all initiatives that drive workforce development, and ultimately business results, comes down to how self-directed workers are. AI is a tool that can inspire and continue to encourage that mindset and behavior, and enable ownership and accountability for growth and contribution to the business.”
A great benefit of AI-assisted training is the facilitation of individualized learning plans, says Elliot Dinkin, president and CEO at Cowden Associates, Inc. “Certainly, one-on-one tutoring is effective for personalized learning, but highly impractical and cost-prohibitive at scale,” he says. “There are solutions that use AI to train and rely upon a process that matches how each individual person learns and then adapts the needs to the experience and skill levels of each learner. This way, the solutions focus only on what people need to learn, and skip what they’ve already mastered. This is beneficial, as it will cut training time and boost knowledge and skill acquisition while also building self-awareness.”
AI can help employees themselves, with support from trainers, to find the career paths that are best for them and their organization, says Mike Hendrickson, vice president, Tech and Dev Products for Skillsoft. “Using data to intelligently inform learners where their aptitude and current skill set could be best utilized will help people re-skill, up-skill, or pre-skill new roles and opportunities in their organization,” he says. “I think there is great promise for remedial suggestions and accurate assessment of a learner’s struggles where we can pinpoint learning assets to help bridge the skill gap.”
The technology might even help ensure the quality of the learning content being delivered, so each employee is assured of receiving the right program to meet his or her needs. “AI could help make sure objectives are clear, not biased, and are measuring what is supposed to be taught. Kind of a balance and veracity check on the delivery of content to a learner,” says Hendrickson. “But more than that, we could use AI to figure out if the instruction is just to meet objectives, or if the instructor is truly teaching the subject in a way all learners understand.”
Meetings 2.0
With so much important interaction and (human) intelligence sharing occurring in meetings, AI can offer support to ensure these gatherings are as effective as possible, says Cory Treffiletti, chief marketing officer of Voicea. “Meetings consist of conversations that drive actions to be taken, but the conversations themselves are a moment in time, and if you aren’t there or you were distracted and missed something, you don’t get the full benefit of the conversation,” he notes. “Our AI platform offers an inmeeting assistant that can listen and help capture notes and actions from a conversation based on criteria you control.”
He points out the ability of the technology to allow employees to go back and review the conversation, and to “stitch together ideas and pieces of conversations into notes that can be shared.”
Like any new technology, and cutting-edge approach, educating decision-makers about the need to add AI to an organization’s workforce management requires a strategy. “You need a champion inside the organization who is capable of introducing employees and leaders to the tool and helping them to understand the impact it can have on the organization,” Treffiletti says. “Typically, the best way to roll out these kinds of systems is to pick a small group that can focus on and integrate a system into their everyday workflow, and allow them to become an extended group of champions inside your organization. They can help evangelize through the organization, and help train others along the way.”
QUICK TIPS
- Use AI to reduce repetitive tasks that require little thought process but can lead to errors when employees are fatigued.
- Give employees help making the right decision. An AI system can show employees what the best decision would be given objective data such as numbers and projected outcomes.
- Use training expertise to guide programming of AI systems, and then train employees to optimize these systems. Trainers can work alongside technology experts in a company to program the AI system to best support employees in their work. Then they can train the employees on how to make the most of the AI system.
- Create individualized learning and career plans. AI can track and analyze employees’ learning progress, so plans can be created that are best for both them and the organization.
- Take bias out of instruction. Trainers can use AI systems to ensure the course content meets the goals of a group of learners and each individual learner, rather than advancing a biased perspective.
- Make meetings more meaningful. AI can enhance employee takeaways from meetings, allowing employees to review conversations, and organize the ideas presented, so the points made become more obvious and easier to act on.
AI and the Future of Workforce Training and Scheduling
By Charles Orlando, VP Marketing, Humanity (www.humanity.com)
Attracting, training, managing, and retaining talent has never been more challenging than it is today, as organizations now exist in an era where real time is the de facto standard. Employee scheduling, training, and retention are key business factors that not only require real-time evaluation and optimization, but also a collaborative effort across the organization. Enterprise workforce management solutions must be capable of pulling and analyzing data and optimizing even the most complex and demanding staff scheduling needs across an unlimited number of locations and departments. These solutions also must be able to forecast scheduling needs based on key performance indicators (KPIs) important to the enterprise to minimize understaffing or overstaffing issues.
The progression of artificial intelligence (AI), machine learning, and Internet of Things (IoT)/smart technology is paving the way for streamlined, personalized training and scheduling. Using AI, the evaluation and analysis of employee data—including behavior, requests, wages, leave, absentee rate, and past work experience—is automatic, allowing technology to quickly and easily assess and recommend tailored training programs much faster than a manager assessment. With AI, managers have access to a 360-degree snapshot of their employees in real time. This insight allows for the enhancement of employee onboarding programs, as well as the creation of custom training and organizational education and ongoing employee development. AI and machine learning make it all a reality.
AI offers enterprises with complex staffing needs the ability to predict training and scheduling needs based on sales forecasts, foot traffic analytics, KPIs, employee skill sets, seasonal demands, and more. Building employee shift schedules based on business-critical data is at best time-prohibitive, if not nearly impossible. AI introduces sophisticated data analysis to the training and scheduling process, allowing managers to make informed staffing decisions based on real-time analytics. With advanced smart features, AI helps resolve conflicts quickly, automatically identifying overlaps in staffing, alerting managers to real-time changes to weather, traffic, and seasonal shifts, and providing up-to-date records of employee availability. In addition, real-time visibility into staff schedules allows managers to identify understaffed busy days—or overstaffed slow days—and manage accordingly.
As AI continues to evolve and play a substantial role in the technology people are using, forward-looking organizations need to leverage solutions that allow them to improve workflow, streamline operations, and enable managers and employees to focus on thriving at their jobs.
Delivering Value in the Future of Work with AI Chatbots
By Natalie Baumgartner, Chief Workforce Scientist, Achievers (https://www.achievers.com/)
The future of work relies on the adoption and integration of the next wave of technological advancements. More specifically, introducing artificial intelligence (AI) into the business results in the ability to gather insights directly from the workforce. As technology progresses, HR professionals will have access to data-backed resources that allow them to continue delivering unmatched services to their organization.
HR professionals have a daunting task in front of them: looking for ways to streamline everything from onboarding and benefits administration to employee assessments and training. AI in the workplace—more specifically AI-backed chatbots—has the potential to shape and improve the future of work.
People need and have a desire for human interaction, and that doesn’t stop with the technology they use daily. Chatbots can grasp the nuances of human-like interactions by learning the user’s actions directly through an active listening interface. This provides a natural and human-like communication that engages the user in deeper, individualized, and personalized conversations. At the same time, chatbots extract data and insights directly from employees that the organization needs to ensure it is addressing the concerns and wants of its workforce.
HR leaders utilizing AI-backed chatbots to their fullest will have the resources to identify gaps in their processes and departments. Using the insights gathered directly from employees, employers can alleviate stressors in everything from onboarding to employee engagement, and even training and development.
Through AI-backed chatbots, employees have a resource to voice their opinions anonymously, and leaders then can address and act on the feedback directly. HR professionals rely on being able to make accurate predictions—predicting who will be the right hire, who will leave, who will excel in their positions, etc. The data from AI-backed chatbots allows for HR practitioners to understand past behavior, sentiment, and roadblocks, and then apply those insights to the workforce—improving the business, culture, and bottom line.
Case Study: AstraZeneca International Region Uses AI-Enabled Training to Drive Sales Growth
By JD Dillon, Chief Learning Architect, Axonify (axonify.com)
Sales is a difficult profession. Medical sales takes this challenge to the next level. Sales professionals must stay up to date on the latest innovations in health care. And they must develop this knowledge independently while traveling between client locations. Finally, they must display unwavering confidence in this knowledge as they engage in detailed product discussions with experienced medical professionals.
AstraZeneca, a global leader in the biopharmaceutical industry, recognized that traditional workplace training no longer fit the needs of its professional salesforce. Its reps just didn’t have the time (or patience) to complete lengthy online modules. And consistently bringing reps to a central location for in-person training was cost prohibitive and ineffective. So AstraZeneca International Region partnered with Axonify to design a continuous microlearning experience that fit into the day-to-day workflow of its salesforce.
In 2015, AstraZeneca International Region launched an adaptive microlearning platform powered by artificial intelligence (AI) designed specifically for the needs of the front-line salesforce. Sales reps have the opportunity to complete daily learning activities using their company-issued tablets. The platform builds a profile for each sales rep, including data on his or her confidence, knowledge, behavior, and business results. AI then is used to deliver a personalized learning activity to the rep. This activity is focused specifically on areas in which the individual rep requires development. These sessions, which take just a few minutes to complete, fit easily into the reps’ busy schedules, such as when they are waiting in a doctor’s waiting room. Reps also have the option to complete additional training or search for information to answer immediate questions.
AstraZeneca International Region focused its development efforts on critical topics, including product knowledge, medical conditions, and sales skills. It quickly saw results that continue to this day. First, 82 percent of the sales team remains engaged in continuous learning, with 24 learning sessions completed on average by each rep per month. They also have demonstrated substantial knowledge growth, with a 37 percent increase in high-priority topics. But most importantly, this new approach to learning has a direct impact on business results. When the business unit exceeded its sales goals for 2018, it leveraged the platform’s impact analysis tools to determine that 25.7 percent of the result was attributed to sales training.