The truth about AI
Rethink what you know about AI
Artificial intelligence (AI) is disrupting industries by introducing new capabilities and shifting how we think about technology.
But not all our ideas about AI are correct. Like any rapidly changing scene, it’s easy for misinformation and misconceptions to take hold. Leaders need to see through the hype and understand the real implications of AI — even as they continue to unfold.
Organizations that can separate AI facts from fairy tales will create new, faster ways of working. Don’t get the wrong idea about AI.
5 common misconceptions about AI
1. AI is a job replacement tool.
Robots are not coming to take our jobs. Sure, AI can automate tasks. But it’s better for augmenting human abilities than replacing them. And while upskilling could slow future hiring, that’s not synonymous with job replacement.
In an AI-enhanced future, your top performers will need a blend of technical acumen and “soft skills.” Employees will need stronger data literacy and algorithmic understanding to interact with AI systems. But critical thinking and creative problem-solving will be equally important — and irreplaceable by machines. People will need to collaborate harmoniously with AI to drive strategy and innovation.
Organizations can ease some of the apprehension around AI. Adopt a positive mindset from the top and be transparent about use cases and applications the organization is exploring. Focus on the benefits to employees, as well as customers and other business metrics. And share success stories whenever AI enhances job roles.
2. AI has all the answers.
There’s a misconception that computers, including AI systems, are always right. We assume that software programs are more objective and accurate than human thinking. That’s not always true.
Remember: AI systems were created by human developers and (mostly) trained on data that humans created. They carry the same inherent biases that we do.
That doesn’t mean AI is automatically unreliable, either. It means that AI tools need to ingest diverse sets of data. And data needs to be rigorously vetted for quality before it’s accepted as fact.
AI systems also need to be continuously monitored to detect and correct biases. Human critical thinking and intuition are some of the best tools to gut check AI responses. Organizations need to create clear lines of accountability and make sure human oversight is an integral part of every AI deployment.
3. AI is complicated and expensive.
There’s a notion that AI requires massive resources and specialized skills that only the largest corporations can afford. AI integration seems complex, costly and possibly out of reach.
In truth, one of the most exciting things about AI is that you don’t have to be a tech expert to use (or even create) AI tools. AI technology is so user friendly that most people could create custom GPTs (generative pretrained transformers) with only a little bit of homework.
The “entry fees” are relatively low, too. Organizations can add tools and capabilities incrementally to keep complexity and cost in check.
4. Only tech experts use or benefit from AI.
There are some tools you shouldn’t wield if you don’t know how to use them — but AI isn’t one of them. Organizations don’t need to completely understand AI to start using it or to benefit. Hands-on is one of the best ways to learn AI.
And everyone should learn about AI. Executives and functional leaders especially should understand the practical applications of AI so they can leverage it in daily work and strategic decisions. Leaders don’t need to know all the technical details, just enough to demonstrate what’s possible. However, they do need to understand ethical considerations surrounding AI, such as data privacy, bias, transparency and accountability.
Companywide, a holistic training and upskilling strategy can uncover new applications. Cultures that foster continuous learning are well suited for AI, regardless of their industry or initial tech savviness. Organizations with dynamic and continuous learning programs have a better chance of keeping up with AI as it changes — and using it to get ahead.
5. AI isn’t appropriate for high-touch industries.
There’s some concern that AI will depersonalize experiences, especially in high-touch services like healthcare or customer service. This is false.
In fact, AI can enhance customer relationships and interactions. Some of the most promising use cases are in customer experience. Data analytics can be applied to tailor communications, personalize offers and speed up service responses.
High-touch industries need to understand their customers better. With good data management practices, AI can deliver deeper customer insights and create tailored experiences.
How Wipfli can help
Are you ready to jump on the AI train? It’s moving fast.
Wipfli can help you find the right areas of the business to add AI, where it can have the strongest strategic impact and add the most value. We focus on pragmatic opportunities rather than hype. Our technologists align AI to your business goals and company culture, so your IT investment takes off. To learn more, see our strategic AI services page.
