Organizations in the industrial sector find themselves at a crossroads. They can successfully embrace artificial intelligence or put the very existence of their business at risk.
It seems like business leaders in every industry are buzzing about AI. The question is, are they simply adopting AI-driven tools, or are they creating an environment for authentic intelligence?
Achieving authentic intelligence means striking the ideal balance between AI and human intelligence. Here’s how your business can use authentic intelligence to stand out in a world where AI is everywhere.
How to Distinguish Your Organization While Taking Advantage of AI
The question of whether companies should use AI has already been answered: Your business must adopt artificial intelligence tools to survive in today’s environment. There’s no putting the genie back in the bottle — AI tools are now necessary for basic business survival.
Businesses realize the value artificial intelligence provides, and decision-makers aren’t about to pump the brakes. The good news is that the AI race isn’t merely a matter of who has the latest and greatest tech. Differentiating your business is all about achieving harmony between your staff and AI tools.
If you think using ChatGPT to write emails will give you an edge, think again. Every other company is doing the same. What will set your organization apart is its ability to deploy AI strategically while maintaining a distinctly human touch.
The Role of People in AI Implementation
Where do your team members fit into the AI implementation strategy? To answer that question, the first step is to identify areas where human intelligence outperforms artificial intelligence. Some examples include:
- Critical thinking and contextual judgment
- Emotional intelligence and leadership
- Creativity and innovation
- Ethics and decision-making
Artificial intelligence tools can process enormous volumes of data and yield actionable insights in seconds. GenAI can even create well-written and grammatically correct content. However, AI doesn’t offer that personable, uniquely human element. You need a talented workforce to deliver in those areas.
Changing the Mindset Around AI
When exploring business use cases for artificial intelligence, many decision-makers focus on concerns like:
- Automating workflows
- Reducing labor costs
- Improving efficiency and accuracy
- Preventing human error
- Scaling the business
All of these are valid goals. However, they can’t be the only ones motivating AI adoption. Business leaders must realize that culture is the ultimate differentiator. That means training employees on how to work with AI and treating artificial intelligence as a force multiplier, not a workforce replacement.
The Upstream Parable of Reliability
The upstream parable of reliability nicely sums up the AI implementation challenge.
Imagine a river where people keep falling over a waterfall and lifeguards constantly throw buoys out to save the people as they’re falling. This would be reactive — the lifeguards tossing out the buoys would be addressing the problem after the falling swimmers had already reached a point of no return.
Failing to understand the situation and only addressing the symptoms of the problem, the lifeguard might be tempted to optimize the replenishment of the buoys in order to be “efficient” at saving the drowning people.
In this metaphor, the people who are drowning after their fall symbolize the equipment failing on an ongoing basis. The lifeguards symbolize maintenance teams who are reacting to symptoms and failing to understand why they have to handle such a heavy workload. They also don’t understand how to reduce the inflow of new problems.
The lifeguards would be more efficient by being proactive, understanding the source behind the influx of the drowning people — why are they drowning? Is it intentional that they are sliding down the waterfall? If so, should they install warning signs and guide the swimmers out before they drop off? Or perhaps the falls are accidental. Swimmers wanted to wade across, but the strong current dragged them along the river.
It’s clear that equipment in an industrial context is expected to operate in a normalized state; this leads to “anticipated failure,” which is addressed with a generic maintenance plan. It’s clear that real industrial conditions can also lead to “unexpected failure,” which results in chaos for the maintenance team.
But this should be avoided at all costs. Companies should avoid equipment failure by fine tuning maintenance and operations in order to develop more predictable, lengthy lifetimes (precision maintenance). If the equipment starts to fail; it should be detected and anticipated in time to prevent disruptions (predictive maintenance).
It’s clear in the metaphor above that no one wants another person to drown. In the interest of saving people, decision-makers might build bridges to prevent individuals wading through unsafe territory. And if risks are unavoidable, preparation is essential.
Consider whether you are equally proactive in your maintenance practices. Do you aim for “zero breakdowns” and “first time right”? Or do you settle for a suboptimal state?
Why Your Business Must Master Authentic Intelligence
Since GenAI is dependent on the maturity of your organization and documentation, it should be seen as a booster of your current capabilities.
Do you simply want to boost a suboptimal state, introducing risky scenarios where AI is driving bad practices/decisions based on poor quality in maintenance practices and/or data? Or do you want to combine AI adoption with the development of a precision culture in which AI can flourish?
Within a few short years, businesses that haven’t fully embraced AI will likely be struggling. Some may even go bankrupt. The benefits of AI will be more evident in mature organizations, which means the introduction of AI has the potential to “polarize” business performance.
The future belongs to companies that treat AI as a way to augment human potential!
This is a do-or-die moment. How will your company respond?
This article contributed by Tom Rombouts, Reliability Director