We simply took a system that was already at its limit and added another layer to it!
The Great Acceleration (Die Große Beschleunigung)
This is the title of a book by Christian Stöcker (Die Große Beschleunigung: Climate change, digitalization, economic growth - how we can hold our own in an exponentially changing world |
https://amzn.eu/d/a77rREs)
A key topic of the book is the exponential growth and rapid change that we are currently seeing and have seen in recent years. For people, but even more so for entire cultures or companies, it is a challenge to understand and manage such changes. The rapid pace of change in today's world has far-reaching consequences for the economy and for companies. Christian Stöcker mentions the following in the context of artificial intelligence, for example:
- Technological disruption: Progress in technologies such as generative AI is driving change. Companies must continuously integrate new technologies in order to remain competitive.
- Lack of skilled workers: The demand for qualified employees is increasing, particularly in areas such as IT and data analysis.
- New business models and processes: Digitalization often requires a complete realignment of business models and internal processes. This can lead to an increased workload and the need for constant reorientation.
- Regulatory requirements: New laws and regulations, such as the AI Regulation, the EU AI Act, pose challenges. Companies must ensure that they meet these requirements.
- Cultural change: The changes brought about by artificial intelligence / GenAI also require an adaptation of the corporate culture. Flexibility, a willingness to innovate and a new form of employee management are becoming increasingly important.
These facts show that in a rapidly changing world, companies not only need to work faster, but also smarter.
The article
Capitalism in the mistrust trap by Michael Hüther follows the same line. The high rate of change and the constant emergence of new pseudo-innovations creates enormous pressure on companies. In the medium and long term, this can lead to an exhaustion of resources and the workforce.
Gartner, where do we stand?
The Gartner Hyper Cicle is a good indicator / orientation for innovations.
The Hyper Cycle is a graphical representation of innovative topics in five phases. It shows the maturity and acceptance of new technologies.
- Innovation trigger: A technological breakthrough arouses interest and generates media attention. Often there are no usable products yet and the commercial feasibility is unproven.
- Peak of Inflated Expectations: Early successes and exaggerated expectations lead to hype. Many companies show interest, but there are also many disappointments.
- Trough of Disillusionment: Interest declines as the technology fails to meet high expectations. Some providers fail or withdraw.
- Slope of Enlightenment: The benefits of the technology become clearer and better understood. Second and third generations of products appear and more companies begin to fund pilot projects.
- Plateau of Productivity: The technology is widely adopted and its market relevance becomes clear. It is now widely used and brings measurable benefits.
Hyper Cycle help to separate the hype from the actual drivers of a technology and make well-founded decisions about technology investments. As far as artificial intelligence / GenAI is concerned, it looks like this.
2023 - 2024 shows we are entering the field of disillusionment / the valley of disappointment:
- Poor data quality: Many projects fail due to inadequate and incorrect data.
- Escalating costs: The development and implementation of GenAI models is expensive.
- Unclear business value: Companies have challenges proving the business value of GenAI projects.
GenAI solutions, such as Microsoft Copilot or Google Gemini, are currently in several Hyper Cicle phases simultaneously. It is still an innovation trigger that causes amazement, especially among people who are less tech-savvy. This still leads to Peak of Inflated Expectations. Employees in this phase name use cases that GenAI solutions will not be able to achieve in the foreseeable future. Example:
- Suppliers should be regularly evaluated by an AI with regard to their quality. The AI should analyze relevant complaints and take them into account in a summarized evaluation. In doing so, the AI should be guided by the supplier's previous assessments and automatically inform the supplier of any changes to its status.
- The AI should evaluate and analyze commodity index data available online in order to make forecasts about the current and future price and supply situation.
- An AI application that comprehensively checks applications for guidelines and evaluation criteria and decides whether the application should be approved. The AI also creates a detailed and legally binding justification.
If it becomes clear that such scenarios cannot be implemented by GenAI, at least not at present, the next step is Trough of Disillusionment.
GenAI as an enabling technology
Examples:
- GenAI supports the automation of routine tasks, the creation of content and the analysis of large amounts of data.
- Content creation: Automated generation of texts and graphics for marketing campaigns, for example.
- Personalization: Optimization of advertisements and customer segmentation for targeted marketing measures.
- Chatbots and digital assistants: Support in customer service and internal processes.
- Program code generation: Automated creation and improvement of software code.
Reality check
Here are two further examples that clearly show that we are still at the beginning with some of the new solutions:
Neither of these examples are general showstoppers. However, the expectation of users and companies is that new solutions will bring benefits and simplifications rather than having to fulfill conditions. This is the kind of thing that puts people off in the first place.
But - and there is almost always a “but”
There is a silver lining on the horizon. The topic of GenAI is becoming more and more mainstream. Together with LinkedIn, Microsoft has published the
2024 Work Trend Index Annual Report.
The most important findings as to why GenAI will become established were summarized as follows:
- Employees expect AI in the workplace because they already know and use the apps from their private lives.
- AI raises the bar for employees and breaks down career barriers.
- A type of AI power user is emerging that will play a special role in the future.
For details see also:
GPT - here to stayThe key point is...
... that GenAI is not a no-brainer in companies either. When Facebook came along and social intranets became a trend in companies at the same time, people often said: “Nobody needed training for Facebook either. So why should that be necessary for our social intranet?”
As many will remember, training and implementation concepts were necessary for social intranet projects to be successful. It's exactly the same with GenAI.
Ok, there are exceptions - here's one:
- AI can help to minimize less demanding tasks so that employees can focus on more important and essential activities.
This is derived from the 𝙀𝙢𝙥𝙡𝙤𝙮𝙚𝙚 𝙎𝙞𝙜𝙣𝙖𝙡𝙨 survey, which is conducted every six months to gain insights into employee wellbeing and productivity. The survey results show that access to AI can increase employee productivity and engagement. Source and further details:
The Key to a Thriving Workforce? A Smart Approach to AI.
Mind you, “can” and not “must”. And without an adoption plan, this will only apply to a few committed employees.
Companies and IT departments are lagging behind the trend
IT departments, innovation drivers and strategy departments in companies are often still struggling with the switch to cloud solutions with their evergreen approach. In addition, there are the aspects that were explained at the beginning of the article. And now there is also the new topic of GenAI.
Another point is that the self-awareness of employees has changed. Until a few years ago, users used the IT solutions that were made available to them. Today, the motto is increasingly: Isn't there an app for this that we can download and use? In the context of GenAI: ChatGPT <-> Microsoft Copilot or Google Gemini etc.
When users take IT into their own hands and how to deal with it
IT departments can no longer reduce themselves to technology alone. The “strategic consulting” factor within the company is the key to success and acceptance among employees. Multi-speed IT approaches such as “Information Competence Centers” have proven their worth. However, such approaches also require IT or an “Information Competence Center” to take on a new / different role in the organizational chart.
References:
