Leveraging AI for HR: The Sweet Spots are in the Employee Experience Journey
In the most recent February Think2018 conference in U.S., IBM's CEO Ginni Rometty, spoke about this being an `exponential moment' when technology and business together will become disruptors a cycle that typically happens every 25 years. She called out that today, AI as a technology - man and machine together, will create far reaching changes in the way the companies today and the world tomorrow will operate. Like every other function, HR has also been exposed to this transformation and AI enabled technology is the next frontier for Talent solutions. Even as we debate and analyze the pitfalls or benefits of AI, from robots taking away our jobs to faster and more accurate hiring decision support, future focused organizations have already begun experimenting and leveraging AI for richer solutions, higher productivity and personalized talent management. It is now a proven differentiator that keeps talent and therefore their companies, ahead of the competition. The shift to an AI enabled platform presupposes that an organization has started on the digital transformation journey and has some of the basics in place a public or hybrid cloud technology platform, a robust data analytics practice, and an internal mandate of innovation and technology adoption, pervasive with leaders and employees alike. Given that the mobile enabled workforce of today (and tomorrow) is seeking a technology driven positive experience at the work place and approaches it with a customer mindset, it is critical that the HR transformation journey towards AI enabled solutions also evaluates the value of these investments from the lens of Employee's experiences, rather than cost saving. This base approach will also ensure that the right Talent solutions are piloted first, the choice of vendors in the eco-system is made appropriately and the readiness and adoption of a solution is maximized. Six Primary Levers will Enable this Journey.
Strategy & Vision: What work experiences designed through AI enabled technology will generate highest impact in employee value proposition
Technology: What technology enablement is needed to drive the analytics, insights and best-in-class work experiences to employees?
Skills: What Skills are needed in HR and employees to harness the power of data, technology and the ecosystem for an exceptional experience?
Ecosystem: Who are the external partners who we need to leverage to deliver superior experiences for our employees?
Data: What data do we measure & analyze to provide deeper insights into Employee Experience?
Agility & Design: How soon can we make it happen & keep improving through direct employee feedback?
Traditional computing is programmed, rules-based, logic-driven and dependent on organized information, but cognitive systems are predictive. Cognitive systems can understand unstructured information such as the imagery, natural language and sounds in books, emails, tweets, journals, blogs, images, sound and videos. They unlock meaning because they can reason through it, giving us new insights to consider. Cognitive systems also learn with each transaction, build their own expertise so we can immediately take more informed actions. And they interact with us and our customers, leading to unique user experiences.
Cognitive solutions therefore have the most impact in situations where decisions require highly complex data sources and a wide variety of inputs, or when they are leveraged for systems frequently used by its target audience. The adoption is further accelerated when the outcomes are customized and personalized to the individual needs of the workforce.
Several Different Levers of AI Enabled Technology Combine to Add Value to Talent solutions.
Recommendation Engines
These algorithms analyze data and make a recommendation as per user's interest. These could be leveraged for curating Learning Recommendations in online platforms, as one example. The key benefit would lie in being able to personalize learning and provide consumable content as per learning preferences, leading to higher retention.
Natural Language Processing
Ability to understand human speech as it is spoken. Given that a large amount of data is generated through text and spoken words, there is ample scope to leverage this technology from resume filtering to sentiment analysis and engagement surveys. Key benefits come from eliminating decision making biases that come with processing unstructured data to a large extent. Resume filtering is most popular where using voice & face recognition software, this technology lets employers compare a candidate's word choice, tone and facial movements with the body language and vocabularies of their best hires.
Machine Learning Systems
Ability to learn and improve without explicit instructions. We have all heard about teaching AI enabled machines that then `learn' to interact. The benefi ts of the technology can be leveraged for chatbots and areas like onboarding assistance or even for basic career advice, where the machine `learns' and then `interacts' as per the training provided by subject matter experts
Predictive Analytics & Decision Support Tools
Predicting outcomes using statistical algorithms and machine learning. Smart alerts can use engagement data & machine learning to automatically identify employee populations that are at risk of leaving. It can monitor and find patterns across millions of data points, generating real time alerts for employees that are at risk of attrition, decreased performance or change in other key indicators. Managers and HR Partners alike can be proactive in workforce planning as well as talent retention when leveraging machine learning enabled predictive analytics.
Through all these solutions, it is important to understand that AI in HR is not a silver bullet. The benefits will need to be derived, and it takes the same degree of tenacity, conviction and change management effort as any major transformational initiative. Organizations that have started the journey also report significantly improved talent metrics, better quality of hire with higher retention, more accurate employee voice & sentiment analysis, higher degree of predictability in turnover & productivity losses, and enhanced learning for future ready skills. At the same time, for the sceptics in the audience of IBM's Think2018, Ginni was able to monetize the value of IBM's Watson HR solutions annual savings at more than $100 billion dollars. Even from a cost perspective, HR functions can no longer afford to ignore the possibilities of AI in HR, and remain a weak link in the chain.
Agility & Design: How soon can we make it happen & keep improving through direct employee feedback?
Traditional computing is programmed, rules-based, logic-driven and dependent on organized information, but cognitive systems are predictive. Cognitive systems can understand unstructured information such as the imagery, natural language and sounds in books, emails, tweets, journals, blogs, images, sound and videos. They unlock meaning because they can reason through it, giving us new insights to consider. Cognitive systems also learn with each transaction, build their own expertise so we can immediately take more informed actions. And they interact with us and our customers, leading to unique user experiences.
Cognitive solutions therefore have the most impact in situations where decisions require highly complex data sources and a wide variety of inputs, or when they are leveraged for systems frequently used by its target audience. The adoption is further accelerated when the outcomes are customized and personalized to the individual needs of the workforce.
Several Different Levers of AI Enabled Technology Combine to Add Value to Talent solutions.
Recommendation Engines
These algorithms analyze data and make a recommendation as per user's interest. These could be leveraged for curating Learning Recommendations in online platforms, as one example. The key benefit would lie in being able to personalize learning and provide consumable content as per learning preferences, leading to higher retention.
Natural Language Processing
Ability to understand human speech as it is spoken. Given that a large amount of data is generated through text and spoken words, there is ample scope to leverage this technology from resume filtering to sentiment analysis and engagement surveys. Key benefits come from eliminating decision making biases that come with processing unstructured data to a large extent. Resume filtering is most popular where using voice & face recognition software, this technology lets employers compare a candidate's word choice, tone and facial movements with the body language and vocabularies of their best hires.
Machine Learning Systems
Ability to learn and improve without explicit instructions. We have all heard about teaching AI enabled machines that then `learn' to interact. The benefi ts of the technology can be leveraged for chatbots and areas like onboarding assistance or even for basic career advice, where the machine `learns' and then `interacts' as per the training provided by subject matter experts
Predictive Analytics & Decision Support Tools
Predicting outcomes using statistical algorithms and machine learning. Smart alerts can use engagement data & machine learning to automatically identify employee populations that are at risk of leaving. It can monitor and find patterns across millions of data points, generating real time alerts for employees that are at risk of attrition, decreased performance or change in other key indicators. Managers and HR Partners alike can be proactive in workforce planning as well as talent retention when leveraging machine learning enabled predictive analytics.
Through all these solutions, it is important to understand that AI in HR is not a silver bullet. The benefits will need to be derived, and it takes the same degree of tenacity, conviction and change management effort as any major transformational initiative. Organizations that have started the journey also report significantly improved talent metrics, better quality of hire with higher retention, more accurate employee voice & sentiment analysis, higher degree of predictability in turnover & productivity losses, and enhanced learning for future ready skills. At the same time, for the sceptics in the audience of IBM's Think2018, Ginni was able to monetize the value of IBM's Watson HR solutions annual savings at more than $100 billion dollars. Even from a cost perspective, HR functions can no longer afford to ignore the possibilities of AI in HR, and remain a weak link in the chain.
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