How AI is Giving Every Employee a Voice Without Having to Ask
For this week’s Workplace Intelligence Newsletter, I interviewed Kevin Bobowski, Chief Marketing Officer at Aware, the leading AI Data Platform for Employee Listening. In his role, Kevin is responsible for the company’s go-to-market strategy, including brand marketing, product marketing, demand generation, field marketing and sales development for their full suite of solutions. Kevin has nearly 20 years of SaaS experience and was most recently the CMO of Siteimprove.
In our conversation, we discussed how executives have been impacted by AI, how to responsibly manage AI in the workplace, and using AI to give employees a voice. We also explored how AI builds trust between employee and executive, and how companies are harnessing AI to capture real-time employee feedback to improve employee engagement and the customer experience.
Read on for Kevin’s insights about this important topic. And be sure to join us during our LinkedIn live event on July 17 at Noon PM EST, where we’ll continue our discussion.
Artificial Intelligence is already changing the business landscape. About two-thirds of current jobs are exposed to some degree of AI automation, impacting 300 million full-time jobs. Companies are scrambling to understand how to leverage it. What advice can you offer to peers in the market seeking to navigate this change?
Face it. AI will transform every industry, business, and job function so everyone must learn to leverage this technology. It’s no different to how people might have thought about other emerging technologies (e.g., mobile) of the past. The promise of AI is mesmerizing but don’t be too ambitious in your application of AI. Yet. Instead, look for “low-hanging fruit” to improve what you are doing today. These projects have a higher degree of success than large, ambitious projects.
Take employee surveys as an example. Surveys have been used for years to capture the voice of the employee, but twice-a-year surveys just don’t cut it anymore. Our world is moving too fast.
Instead, Aware customers use our AI Data Platform for continuous employee listening to get a real-time pulse on daily operational challenges facing employees, their concerns, reactions to company and global events and even concerns about the impact of AI on their jobs. It’s a continuous feedback loop giving employees a stronger voice – and managers real-time actionable insights.
Ironically, it’s AI that is giving employees a new, more powerful voice. And insights from the collective voice of the employee are helping managers respond and react—in real time— to the concerns of their workforce.
What is “Responsible AI” and what is the responsibility of the business when it comes to the ethical implementation and use of AI in the workplace?
Responsible AI starts with good data because AI models are only as good as the data used to train them. It starts with the decisions on how you train the model and the data sources feeding it. You must be thinking about the data sources you use on day 1.
Large language models need massive volumes of data for training and building generalized models. However, you may not know what data went into any individual result coming out of it. You have no idea how it will respond to types of content or questions. For this reason, these models may introduce bias, lack of context, or deliver inaccurate outputs that lead to poor decisions.
Responsible AI may use smaller models trained on what you know, the data you understand, and the results you want. That delivers high-quality, responsibly built models. The data used to train these models is targeted and specific to solving real use cases. When a CEO is making a business decision about the business using the insights from AI, accuracy and context truly matters.
We live in a dynamic, constantly changing world. This means that once you create a model, it is immediately out of date. The ability to refresh AI models is key to keeping them useful and valuable. At Aware, we're focused on business use cases and how our data is interpreted. The models that provide a single interpretation, something like a sentiment model, can be small. This allows them to be retrained rapidly to adjust to the market, to adjust to new customers, to adjust to the way language is being spoken in a much quicker way than a large language model.
The final component of Responsible AI is data governance or access to data. Role-based access control (RBAC) is a method of restricting access to data based on the roles of individual users within an enterprise. This limits user access to only the data and systems they need to do their jobs, which helps to protect sensitive data and systems from unauthorized access. RBAC can help to improve compliance with security regulations by providing a clear and auditable way to control access to data and systems.
Responsible AI is a complex topic, but it is essential for organizations that are using AI to make these decisions about the business they run. By following the principles of Responsible AI, organizations can ensure that their AI models are accurate, unbiased, and safe to use for making business decisions.
How can AI give employees a voice and how can leaders use that information to make better decisions, especially during difficult times?
The pandemic spurred the mass-adoption of collaboration tools like Slack, Teams, and Zoom. The office water cooler went digital, and today these tools contain so much more than just shop talk. They’re a real-time pulse on the sentiment of the workforce and the topics that matter most to your employees—if you can access the data in a meaningful way.
In a world moving at lightning speed, it’s more important than ever that employers listen to their employees. Twice-a-year surveys just don’t cut it anymore. Surveys are slow, expensive, and packed with bias, from deciding what questions to ask to deciding how honestly to answer. In collaboration conversations with colleagues and peers, employees say what they’re really thinking and discuss the topics that really matter to them. Aware helps business leaders to visualize those insights at scale, providing a real-time pulse on the business that you can’t get anywhere else.
There’s an eroding trust between executives and employees right now. How can AI and employee voice build that trust back?
Trust is the foundation for building strong teams, creating a positive work culture, and producing results. Failing to build a foundation of trust within a company has a tangible impact on its performance and productivity. Fast Company shared a story of one Fortune 500 enterprise that took twice as long to execute changes as a direct result of mistrust.
Lack of trust is as much a problem at an individual level as at corporate level. According to the new Edelman "Trust Barometer" (a survey of 33,000 people in 28 countries), one in three people don’t trust their employer. They also discovered that trust decreases from top positions to the lowest. For instance, 64 percent of executives trust their organizations, while only 51 percent of managers and 48 percent of other staff stated they trust their organizations. Employees remarked that they trust their peers more than the CEO and upper-level executives of their company. That means the higher up you go, the more critical it is for you to build trust with those beneath you. Building trust starts with leaders.
Aware’s AI data platform helps leaders build that trust because it gives them accurate, real-time insights into what matters to their employees at every level. In a world where executives are so often (rightly!) accused of being out of touch, Aware helps the people at the top see immediately what matters to those on the front lines and what they wish their leaders knew.
How are your customers using employee voice data, captured by AI, for real-time feedback and decision making?
There are so many exciting use cases for the data our AI platform creates, precisely because it is so closely curated. At the highest level, we’re giving leaders a 360-degree overview of the sentiment of their workforce and the topics that matter most to employees. They can use those insights in a hundred different ways—to improve top-down messaging, adjust the benefits they offer, or proactively address the causes of toxicity within their company.
For example, one of our customers rolled out a Daily Pay feature for their frontline workers, so they could get paid right after they finished a shift. Leaders were really excited about this feature, but on their internal comms channel any mention of it was met with angry emojis and low sentiment—but nobody spoke up and said why they weren’t happy with it. Using Aware, they found out that the feature wasn’t set up correctly on the banking side, and employees didn’t understand the training they’d received on how to use it. Aware gave the company the information it needed to rectify the banking problem, offer additional training, and get the roll out back on track.
We live in an always-on world, where global events have local impact and employee sentiment can shift overnight. Employees want their bosses to listen to them. They expect the company they work for to understand what topics are top of mind and to respond in a timely manner when they raise concerns or complaints. Proactive leadership is a hallmark of a company that cares, and that’s exactly what Aware enables through AI analysis of employee voices at scale.