With the introduction of generative language model ChatGPT and other AI platforms such as DALL-E in 2023, the revolutionary and sophisticated algorithm has become a household name.
AI algorithms creates opportunities for businesses to improve efficiency, streamline operations, reduce production costs, and meet company objectives.
BusinessBecause spoke to Brian Pentland, an Information Systems professor serving as faculty in the Full-Time MBA and Executive MBA programs at Michigan State University’s (MSU) Broad College of Business, to discuss how AI will affect businesses, what its limitations are, and what the future looks like for businesses.
How is AI already impacting businesses?
While the strides we’ve seen in AI in 2023 appear revolutionary and game changing, companies across the world have already used groundbreaking algorithms for decades.
“The way business and our economy are designed is tightly integrated with algorithms for planning, design, for everything,” Brian says. “When I send an email, I don't know how to route the email to the UK—an algorithm controls that.”
AI is an algorithm, collecting data already created. Brian believes it’s helpful to use the term algorithm rather than AI to avoid it becoming too ‘sci-fi’, helping this technology to remain accurate, descriptive, and firmly planted in reality.
Today, companies of all shapes and sizes are reaping the benefits of big data and analytics, pattern recognition, and automation.
Businesses commonly leverage AI algorithms to sift through and analyze customer data within cloud software platforms such as Salesforce. This practice enables the extraction of real-time insights from the data, which helps to enhance operational efficiency.
Automation, such as deploying driverless vehicles in factories or using software to check and approve employees’ expense claims, is another increasingly common way to speed up routine tasks and makes these easier to perform.
Why we should be talking about AI differently
Brian explains the hype circle, a concept created by the Gartner Group, that surrounds the invention of these exciting new technologies.
“Some new thing comes along, and everybody goes crazy. There is huge hype, but it is followed by disillusionment,” Brian explains.
This is what Brian feels is happening with AI: we are right at the peak of inflated expectations and sometime soon we will fall into the trough of disillusionment.
After the trough of disillusionment these innovations eventually go into a plateau of productivity, when an ecosystem of products, services, business models, and workforce co-evolves with the innovation itself.
Brian explains that with this revolutionary, innovative technology, we tend to overestimate the short-term impact and underestimate the long-term.
“Think about internal combustion engines: replacing horses with cars. First it just looks like a substitution, but then there are all kind of effects: more travel, growth of suburbs and commuting, and climate change.”
For businesses to effectively use AI to evolve longstanding processes, Brian explains that organizations need to understand the basics of the tools they are working with, such as the opportunities and limitations of algorithms.
Adapting and innovating through AI advancements
AI is ultimately data sets, and it’s up to businesses and leaders to interpret that data and incorporate it into their business model.
“We have all this data, and a ton of tools. How do we interpret it?”
Brian gives the example of how Large Language Models (LLM), such as ChatGPT. The tool can take a prompt and give a result instantly, such as a song about cheeseburgers in the style of Beyonce.
However, this is only a collection of various data sets, and it’s humans who innovate and turn it into something marketable.
“All we have is some text on a page. If you want to turn that into a hit single, you need a studio and a producer, musicians, and a singer. You need marketing and distribution and branding. Algorithms by themselves can't get off the page.”
Brian emphasizes that AI is not innovative. It can take what we have already and make it into something new very quickly, but it cannot make something new out of nothing, that’s up to us.
“If you maintain a certain stability, then the algorithm is your friend. But if what you want to do is change the conversation or innovate in some way or say something unexpected, then the algorithm is inherently not doing that.”
How can business leaders implement AI?
To garner success from AI, it is important to combine it within a company’s strategies and the people who make the company successful.
“For general business and customer service facing tasks, algorithms need to be wrapped in routines and people to fit with institutions and expectations.”
So how can business leaders wrap this sophisticated algorithm in routine and bring it into business?
“At the end of the day, it needs to be integrated with the practicalities of a business model, the value proposition for a customer. It must fit into that whole ecosystem thinking,” Brian says.
For small businesses, Brian suggests they need to stay up-to-date with changes and adapt, but not completely change their successful methods. It's about finding the right balance between keeping up and staying true to what's been working.
“Smaller organizations will need to rely on vendors who make algorithmic products and services available as the business ecosystem co-evolves with the technology. There are already lots of applications coming on the market, but there’s no magic answer.”
The full potential of algorithms in business are yet to be seen.
Brian concludes that the best way to use AI in businesses is by establishing new ideas and ways of working. He says that real changes in business happen when companies innovate and redesign new processes, instead of just changing existing methods.