‘Generative AI’ and ‘Agentic AI’ are following a longstanding tradition of being buzzwords that generate a lot of hype and expectations, before eventually calming down into realistic expectations.
That’s why this blog takes a look at the buzzwords of the past few decades and how they have been building upon each other to lead us to today’s obsession with AI. Each illustrated with a concrete example from a fictional company called GrillMaster Europe. This will help clarify what’s possible—even for your business.
Big Data
The term ‘Big Data’ began to gain traction as a buzzword in the mid to late 2010s, when companies like Google, Amazon, and Facebook started talking about how they managed and analysed enormous amounts of user data. The Economist wrote about this phenomenon in their article ‘The world’s most valuable resource is no longer oil, but data‘ with a dramatic summary of the situation:
‘…concerns are being raised by the giants that deal in data, the oil of the digital era. These titans—Alphabet (Google’s parent company), Amazon, Apple, Facebook and Microsoft—look unstoppable. They are the five most valuable listed firms in the world. Their profits are surging: they collectively racked up over $25bn in net profit in the first quarter of 2017.’
At the time, a model introduced by Gartner (discussing the ‘three Vs’ of Volume, Velocity, Variety) was widely used to define Big Data.
The natural question resulting from Big Data is ‘But how can I use this data?’ which has led to big data analytics and predictive analytics. Classic examples of predictive analytics include things like pipeline forcasting and product recommendations. As the programming of AI engines becomes more advanced, these predictions become more accurate and can be applied to other areas of business.
GrillMaster Europe:
- Peak of Inflated Expectations: When Big Data was first hyped, GrillMaster Europe expected it to remove ‘gut feeling’ from business decisions, allowing accurate sales forecasting, uniquely personalised experiences, and vastly improved efficiency.
- Trough of Disillusionment: They quickly realised that in order for data to add value, it needs to be accurate data. And the rate of data decay is higher than GrillMaster Europe could keep up with. On top of this, consumers started to worry about privacy and who was the true owner of their data.
- Plateau of Productivity: Today, GrillMaster Europe uses their loyalty program to collect data on their customers, ranging from demographic data such as their birthdate to behaviour data such as how often they purchase. The GrillMaster website collects data on visitors and what products are typically purchased together. And the GrillMaster ERP system stores vast amounts of data on their supply chain, inventory, and returns.
Internet of Things
The Internet of Things (IoT) reached its peak status as a buzzword in the mid-2010s, as a natural progression of both Big Data and rule-based AI. IoT is defined as physical objects connected to the internet that can collect, send, and receive data. This includes everything from smart thermostats and security systems to connected cars and industrial sensors.
But the limitation for many of these devices came in what could be done with the connection. After IoT had it’s hype moment, it became a running joke how most ‘smart’ devices are actually quite dumb. Which is because these systems are often dependent on rule-based AI.
Rule-based AI (also known as decision logic or if-this-then-that rules) is a simple and widely used form of artificial intelligence in which the system operates based on predefined, programmed rules: ‘If X happens, then do Y.’ These systems are not self-learning and do not adapt based on data or experience. They respond solely to fixed conditions or scenarios set by humans.
GrillMaster Europe:
- Peak of Inflated Expectations: With the Internet of Things, GrillMaster Europe expected to realise a previously unachieved level of automation in the factory, with sensors determining everything from product quality to equipment maintenance needs, and then acting accordingly.
- Trough of Disillusionment: After some initial pilots, GrillMaster Europe realised that the raw data output from sensors does not always equal intelligence and that human input was often still required.
- Plateau of Productivity: Today, GrillMaster Europe has simple IoT solutions, such as the security system that automatically sends an alert and calls the police when doors are opened by someone without permission.
Personal Assistants
‘Voice assistants’ reached buzzword status due to the release of Siri in 2011 and Alexa in 2014, but the technology behind these is more commonly referred to as Natural Language Processing (abbreviated as NLP). It began with Google’s ability to understand what you were searching for (despite all your typos and lack of real sentence structure) and evolved into highly sophisticated voice-activated phone menus and customer support hotlines.
NLP is one type of AI that focuses on the interaction between computers and human language. It enables computers to interpret and respond to human speech and text in a way that resembles how people communicate.
It was also the first example of technology talking back to us, and has prompted articles such as this one declaring that ‘falling in love with a bot is inevitable.’
GrillMaster Europe:
- Peak of Inflated Expectations: The initial hope was replacing the entire customer service team with voice assistants that could process simple questions, freeing up these staff members to focus on sales or order processing.
- Trough of Disillusionment: Many customers changed to another vendor when they realised they could not reach a person at GrillMaster Europe, and the phone system often gave people the wrong information.
- Plateau of Productivity: Today, the initial greeting when calling the main GrillMaster phone line asks people to briefly explain why they are calling and then directs the call accordingly to a real person.
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Deepfakes
In 2017, the term ‘deepfake’ was first coined by combining ‘deep learning’ (a subset of AI used for pattern recognition), and ‘fake’ (referring to manipulated media). Fake videos of politicians prompted panic about what AI could generate in terms of misinformation, and a call for regulations in the industry. While this was several years ago, it was the precursor to modern AI-generated videos, which not only create convincing images but also generate voices and messages.
GrillMaster Europe:
- Deepfakes were primarily a topic for journalists, media, and politicians, so GrillMaster Europe did not have any expectations.
Self-driving cars
Between the DARPA Challenges and Google’s Self-Driving Car Project, the hype of self-driving cars had its moment around ten years ago. One cause of the hype was a focus on improving computer vision, a form of artificial intelligence that enables computers to ‘see’, analyse, and respond to visual information—such as live camera footage, videos, or images of faces, products, or barcodes—in a way that resembles how humans perceive and interpret with their eyes and brains.
GrillMaster Europe:
- Peak of Inflated Expectations: GrillMaster Europe had high expectations for self-driving cars, and hoped to replace all their truck drivers to improve safety and protect supply chains.
- Trough of Disillusionment: The complexity of full autonomy (especially in urban environments) became clear. And there was never a product available for GrillMaster Europe to invest in.
- Plateau of Productivity: Today, they have upgraded their trucks to include lane assistance and adaptive cruise control. They also implemented the use of some automated guided vehicles (AGVs) in the warehouse.
ChatGPT
Which brings us to the latest hype cycle of generative AI, prompted by the release of ChatGPT. Generative AI is a form of artificial intelligence that creates new content based on what it has learned. Unlike the forms of AI mentioned above—which primarily analyse, classify or make predictions based on existing data—Generative AI is capable of producing original data, such as text, images, music, code, or video.
GrillMaster Europe:
- Peak of Inflated Expectations: GrillMaster Europe is currently in the phase of inflated expectations for generative AI, with hopes that it will handle everything from writing personalised marketing content and creating how-to videos to automating the customer support chatbot on the website.
People are starting to realise that AI is not going to solve all problems—it is too dependent on the quality of the input provided and has a tendency to make things up—but the potential is there for AI to result in significant business improvements and become integrated into our daily lives. We do not yet know all the ways that AI will be used, and what will be the new plateau of productivity, but we do know that it will happen.
The good news is that AI is changing the way we do business. The even better news is that you are probably already ‘doing something’ with AI in some form. But the challenge is in how to get started, and what form of AI is truly helpful for your business.
