The Fourth Industrial Revolution. The megatrend of the 21st century. The revolutionary solution to all the world's major problems. The predictions and claims do not lie: AI is taking the world by storm and will renew and improve everything. That is an exciting vision of the future, but to what extent does AI already have real business value for your brand or company today?
ChatGPT for text, Dall-E 2 for illustrations, Generative Fill from Adobe Photoshop: the evidence is clear. McKinsey argues that generative AI will unleash the next wave of productivity . Anyone can now create 'something': blogs, scripts, illustrations, product photos, presentations, voice, music, and video. But 'something' does not necessarily mean that the result is something with value.
Generative AI is in the spotlight today, while AI has long proven itself in fields as diverse as healthcare, finance, logistics, retail, energy, manufacturing, legislation, and marketing. AI is particularly good at processing large amounts of data, finding trends and making predictions: machine learning. That's just less immersive and baffling to the public than generative AI.
Is Generative AI really 'the next best thing'?
"Generative AI has created a lot of momentum and many regard it as the next big thing," says Bram Cappaert , Center of Excellence Lead for Strategy at iO.
"But there are still some really big steps to take. Today it is very difficult to distinguish which output is based on demonstrable reality and which is simply made up. AI hallucinations is already causing problems, especially for people who blindly trust the results that language models give us. It's the same with deepfakes: Which is true? The crux will be in creating a context in which we have certainty about the output quality so that we as a company can use it effectively to make decisions, for example."
"AI is a means, not an end. It should always be about solving business problems."
"Everyone talks about AI as hype, but the emphasis should mainly be on the impact for companies," says Raymond Muilwijk , Center of Excellence Lead for Technology.
A typical pitfall he sees is that technology – in this case we are talking about AI – is set as a goal. "AI is then added to a product or service purely for marketing or image purposes. But ultimately, AI as a tool is about transforming the way you can solve business problems. According to McKinsey, 75% of the use case value that generative AI can deliver will fall in four areas: software engineering, R&D, customer service, marketing and sales."
Fewer no-shows thanks to AI
Customers who don't show up for appointments or reservations in showrooms, hospitals, restaurants, events, or concerts: no-shows are a common problem faced by businesses that cost revenue. AI can help in the form of machine learning by predicting in the customer journey which customers will not show up and then focusing additional communication efforts on those specific people. Currently, iO is working on such a solution for a company in the automotive industry, where sales mainly take place in showrooms. "Is it sexy? No, not really. But fewer no-shows means more turnover," says Bram.
"AI can help predict the customer journey in the form of machine learning so that you as a company can anticipate it."
Better customer service with AI
He gives customer service as a second example. "Because organisations have many different departments with their own work processes and systems, it isn’t always easy to help a customer. ‘I will put you through' is something we are all familiar with, and then you have to tell the next employee your story again. It's extremely frustrating." This is where Generative AI can help by creating personalised answers and solutions throughout the customer journey. Data that is stored in silos is thus made immediately accessible. For example, the customer service department or a self-service portal can help customers get started much faster. And that results in more satisfied customers.
Learn to understand the potential
AI is a technological tool that allows you to create a lot of value. However, the recent call from a group of leading tech experts for a halt to all AI experiments for six months is premature. To quote another prominent thinker, Kevin Kelly, futurist and author of the bestseller What Technology Wants, AI is still in its infancy : "What we now call AI will no longer be considered AI in a few years... In the long run, AI will have a bigger impact than fire and electricity. But the full consequences will only unfold over the course of centuries."
"You can add AI to almost anything. That's called AI-driven," Bram says matter-of-factly. "The question is whether it adds value in the eyes of the user. Whether it concerns consumers, employees, or applicants. That is what ultimately makes a product or service relevant and sought after. Are you solving real problems? Are you answering questions faster and better? And is that process easier than with the competition? AI is a growing part of the solution to a specific problem. But the value is in the application. Organisations need to understand the potential. It's about more than just more efficient content and asset creation. We need to assess which processes can run differently and how the end customer can be better served. Where AI is visible in the showroom today, it will deliver value once again under the hood tomorrow."
"Is your organisation still lagging behind in digital maturity? You're going to have a really hard time."
The adoption of AI is not going to be a gradual process
Not all companies can seize the opportunities presented by AI immediately. Digital maturity is an essential basic condition, says Raymond. "Organisations that have previously deployed composable architectures can now quickly realise AI applications and integrate them into their digital ecosystem. However, if your company's DNA does not yet include digital and tech, the leap to AI will be particularly difficult. Companies just don't have years to keep up. The adoption of AI will not be a gradual process like digitisation has been until now."
"In 2011, it was like, we need an app. In 2018, we have to do something with the metaverse. And now, in 2023, something has to happen with AI, but that is anything but a good business case. Then you just jump from hype to hype. That's window dressing, AI washing, a funny gimmick. Nice for the stage, but not necessarily for the users. It just distracts from the real problems."
"Just doing ‘something with AI’ is not a good business case"
The path to AI is different for every organisation
Organisations that use AI to solve problems are faster and more innovative than their competitors. If you don't use AI, you run the risk of being overtaken by companies that are working with AI. But beware: Without clear business value, AI remains a hollow gimmick.
Raymond advocates a practical approach. "You first need to be clear about what AI means for your organisation at different levels: the need for a distinctive customer experience, a growing demand for internal AI capabilities, the need for change management... Start by focusing on the customer experience, and you will automatically arrive at the technological needs and potential of your organisation. That path is, of course different for every business. There is no standard, one-size-fits-all AI solution. You're really going to have to get going and learn how to apply AI. That is radically different from purchasing a SaaS service with an AI sticker on it."
No time to lose if you want to win
"Do not wait until the big promises about the future potential are fulfilled and AI becomes mainstream", Bram concludes. "You have to act now if you want to learn to use AI as a differentiator. Look at the problems your company is facing today and find practical AI solutions that deliver concrete results so you can stay ahead of the crowd and maintain your relevance in the long term. There really is no time to waste."