Ever thought AI might be overhyped? I get it. A lot of people are talking about artificial intelligence as if it already were this superintelligent digital entity capable of anything and everything. But that’s far from being the truth. That doesn’t mean, however, that AI is useless.
So, it’s worth thinking whether there is a middle ground that just resonates with readers and businesses and is practical. Fortunately, there is (but with a caveat). Let’s dive into it.
The rise of AI
AI is making waves in the business realm. From mainstream coverage to famous LinkedIn gurus with “Steal my AI strategy” type of posts, AI seems to be everywhere. But what exactly is it?
At its core, Artificial Intelligence refers to the simulation of human intelligence in machines that are programmed to think, learn, and problem-solve like humans. It encompasses a wide range of technologies and techniques, enabling machines to perform tasks that typically require human intelligence.
Looking at the clockwork, AI operates through algorithms that learn to map input data to desired outputs, often in ways that aren’t explicitly programmed. These algorithms are trained on large datasets, learning patterns, and structures within the data. Once the training phase is complete, the AI produces outputs that mirror the data it was trained on, but with unique, novel elements.
This ability is powered by its key features, including:
- Capacity for creative problem-solving
So, what does that mean for your business?
AI algorithms are powerful enough to shift through massive datasets, identifying trends and patterns that would take humans months to figure out. This capability allows your businesses to gain deeper insights into your operations and customer behaviors, driving informed decision-making and strategy development. It also delivers tailored, personalized experiences both for your team members and customers.
Whether it’s through tailored product recommendations, dynamic content, or intelligent customer support, AI is redefining the way business is done.
It seems like Goldy tools from a multiverse dimension, but of course, with a cost.
AI trends: Separating hype from reality
In 2022, everything changed. The new AI revolution began and spilled into 2023.
It has become a gold mine and everyone now wants a piece of it or tries to integrate it into their operations. From Embedded AI and UX-focused AI to low-code/no-code AI and augmented analytics to AI coffeemakers and baristas, people will make you feel that, if your product doesn’t have some type of AI in it, you’re living in the Stone Age.
The reality is: Not everything that has AI in it improves your business operations. Not all that glitters is gold. If you haven’t lived under a rock, you’ve noticed a huge surge in AI website builders with their low-code or no-code capabilities. It’s a great democratization of AI but you have to question the quality of the output and to which extent it completely fulfills your needs as a business.
The same goes for augmented analytics and embedded AI.
All dangle a promise of enhanced user experience and seamless integration on a stick in front of you. But they come with a catch.
These are the three main traps most businesses fall into when adopting AI into their operations:
- They just adopt it without much forethought and strategic approach, going with the “Just trust me, bro” mentality.
- They think that. just because it’s AI, it will govern and teach itself with little to no human training or oversight
- They implement it once and forget about it. It’ll work forever, right?
AI in business: The insights
The first roadblock you’ll face with incorporating AI into your business is ethics — people trust people, not some AI out there.
AI significantly boosts your business processes, but it also inadvertently perpetuates biases and unfair practices if not carefully monitored and adjusted. Your AI integration must be fair, transparent, and accountable. That’s why ethical considerations must be embedded from the moment you plan on integrating AI.
As I’ve mentioned and soon you’ll feel it on your skin, it’s a common misconception that AI is a self-sustaining tech. Most businesses don’t see it yet, but the success of AI is heavily dependent on the knowledge and skills of the people who use and manage it. You should include everyone in the basic training of AI and its implications, not just the senior execs and team members.
Besides ethics and training, you have strategic implementation to take care of. The third issue has three components:
- How to successfully implement AI so as not to jeopardize jobs.
- How to retain privacy .
- How to escape the claws of tech dependence.
Master those three and you’ve integrated AI into your business like a real pro!
FLASHY TREND: Don’t fall victim to AI automation. Just because it’s capable of solving complex tasks, it doesn’t mean you have to automate every single task.
AI in action: Real-world business case studies
Successfully implementing AI isn’t just a business tale higher executives like to tell to senior managers. It’s a real possibility!
Take for example Deloitte’s AI Projects, which developed and incorporated AI in various internal and external applications. These projects range from automating routine tasks with taxes and legal to implementing advanced AI-driven analytics in finances, providing practical and valuable insights for decision-making processes.
Another shiny example is Hanson Robotics, which has built humanoid robots with AI technology for the consumer and commercial markets. Sophia, a Hanson robot, communicates effectively with natural language and uses facial expressions to clearly convey emotions, the same as humans.
This article wouldn’t be complete without mentioning Microsoft and their AI tools in Microsoft Azure to understand the conditions and behaviors of their customer success stories. All leading to improved and more thorough decision-making.
But buyer beware!
AI disasters in business happen and can cost you lumps of money and get your reputation on the line! You’ve probably heard about the famous ChatGPT hallucinations in a corporate court trial. Or the one where iTutorGroup jumped on the AI train before properly “configuring” their luggage and destination, costing them a staggering $365,000 in lawsuit settlement just because the AI was poorly configured and played heavily on age discrimination.
Even the big giants like IBM stumble in their path to implement AI. Just because you have a promising AI doesn’t mean all doors are open in any industry you desire. That’s what led to the fall of Watson — a lack of quality data and domain expertise.
AI for businesses: Conclusion
As with every tech, their efficiency and effects highly depend on how you use it. That’s even more thorough with implementing AI into your business.
The importance of ethical AI, AI literacy, and strategic AI implementation can not be overstated, so always approach them critically. The future of AI in business is bright, but it requires a balanced approach where enthusiasm is tempered with critical analysis and responsibility — unless you want to end up in a New York Times story with another AI lawsuit on the court’s table.