Understanding AI

How Organizations Earn Employees Trust With AI

“AI is a tool you use, not a boss you serve.”

Logan Monday

I remember the moment when I realized that AI has nothing to do with technology and everything to do with people. I read a news story in January 2020 describing how iHeartRadio fired 600 employees, simply because an AI program could do the work more cost-effectively. The AI program didn’t fire those people, the company did. The leadership of that company clearly believed that the AI program was a means to improve short-term profits not to pair the tech with their employees for long-term growth. That’s when I realized AI has less to do with technology and more to do with people.

Since January 2020, I’ve been on a journey seeking to understand how AI matters to individuals, employees and organizations. With ChatGPT becoming the first Generalized AI to be used by the public, it’s important that people feel confident working with AI for their benefit as well as organizations bringing AI into their processes with a clear and transparent strategy. Read on to learn how you can use AI in your work or begin implementing it in your organization.

What is AI?

There are many different variations of defining AI but the Department of Defense’s AI Strategy defines it best as, “The ability of machines to perform tasks that normally require human intelligence.” What AI isn’t though, is a one-size-fits all program. Just as there are different players on a sports team, there are different AI programs with different skill sets. Those different programs fall under three categories: Handcrafted Knowledge, Machine Learning and Foundational Models. Let’s briefly look at each category.

Categories of AI

The first category of AI is one everyone has used or is familiar with and that’s Handcrafted Knowledge Systems. They are AI that uses what we think of as traditional, rules-based software that takes the knowledge of human experts, which is codified by software coders, into a long series of programmed “if given x input, then provide y output” rules. This is what’s used in Excel, tax prep software like TurboTax and the famous IBM Deep Blue chess program. As anyone who’s used Excel or TurboTax, it’s maddening if you wrongly input something into the program since the program follows set rules based on the knowledge of the people that codified the program.

Now, Machine Learning, ML, systems are different because their “knowledge” is not programmed by humans. Instead they accumulate their knowledge from data. In turn, that ML program aka algorithm runs on that data, using it as a training dataset and then makes an AI model. Just as sports players come from different experiences, ML uses different datasets to produce different algorithms. There are four types but the main difference between them is if the data is labeled or not. Labeled data produces incredible performance but it can be difficult to acquire. Finally, Deep Learning is a subset of ML that connects multiple algorithms, drastically improving performance.

The newest, and sexiest, category of AI is the one all in the news: Foundational Models. They are gigantic models that are trained on a vast quantity of data with significant task adaptability. In other words, they take data from separate sources and use that data to complete a task. This is what ChatGPT and ChatGPT-4 do. This is why AI matters. Because the tipping point has shifted from organizations needing to create their own AI to one where anyone can use them. A similar shift occurred when the cloud became accessible. The potential for employees and organizations is unlimited, if they prepare for it starting now.

What Generative AI Means for Organizations

The potential of Generative AI is incredible for employees and organizations. It isn’t a gimmick, or a fad, it’s as transformative to organizations as the internet was in the 90’s. Yet, despite its transformative power, the wisdom of traditional project management must be heeded. AI projects will fail not because of the tech, but because of people being unwilling to set expectations, plan the integration into legacy systems, and train employees. That’s why I believe that AI must be thought of not as an engineering software but as a continuous program to be trained. Accenture agrees, “Whether it means training every employee on foundation model capabilities, or creating teams dedicated to integrating these models into different parts of the business, bringing your wider organization into this new era of AI is critical.”

Big Tech is already doing this. According to a Kizen survey asking about AI in the workforce, when employees were shown how they used AI on a day-to-day basis the, “Percentage of respondents who reported using AI on a day-to-day basis jumped from around 40% to 65% after survey respondents were shown examples of the role of machine learning in everyday apps like navigation tools, personalized shopping algorithms, and in products like AirPods.”

Earning Employees Trust With AI

A drawback of AI is that even though it matters, the public narrative of it is that AI will take people’s jobs.

AI isn’t about the technology, even though it’s incredible, it’s about the people using it as a tool. By properly communicating how an AI program will benefit an employee and their department, fears of job loss will be alleviated. Employee buy-in will deepen with training on how to use the AI program, incorporating into their work processes and performance metrics. A recently completed study by the National Bureau of Economic Research supports this stating, “Customer service workers at a Fortune 500 software firm who were given access to generative artificial intelligence tools became 14% more productive on average than those who were not.”

That’s why it’s necessary for organizations to communicate how they’re leading their employees into this transformative new era of AI. As the Harvard Business Review describes it, “Assuming employees understand the changes your company is going through will jeopardize your change initiative. So the next time you’re approaching a change project, be sure to think about how you can inspire, inform, empower, and engage your most powerful ambassadors – and successfully lead your company into the future.”

This is a simple and effective way to earn employees trust with AI implementation. Don’t be like iHeartRadio, who fired 600 employees overnight, who only focused on using AI for short-term gains. Rather, communicate to your employees that there is a clear and transparent strategy involving them with AI, will deepen trust and provide long-term growth. As remarkable as AI is, it’s still a tool for employees to use, not to be replaced by.

Now you know what AI is and why it matters. Just like different sports players bring different skills, experiences and play different positions, AI programs are similar. There isn’t a one size fits all for how best to use an AI program as an employee, within your department, and throughout your organization as a whole. That’s why AI is about people, not just the tech. Just like a coach needs to communicate to their players what they’re doing, training them on how to do it and how it fits into the strategy as a whole, the same is true for implementing AI programs in your work.

I believe that instead of replacing employees, AI serves as a powerful tool, enhancing productivity and streamlining our work. That’s why I provide personal 1:1’s in-order to maximize the benefit professionals will gain from ChatGPT.

Contact me today for a free 15 minute consultation, and share how you want to us AI for your benefit.