ChatGPT has now become established in many organisations. Staff use it to generate text, summarise documents, analyse information, create presentations or utilise AI to assist with day-to-day tasks.
This is an important first step.
But it is not yet an AI strategy.
There is a crucial difference between using a single AI tool and the strategic integration of artificial intelligence into a company. Whilst individual employees use AI to make their own work more efficient, an AI strategy takes the entire company into account.
The key question is where AI can actually create economic value, which processes need to be changed, what data is required, and how people and technology can work together effectively.
“ChatGPT can boost individual employees’ productivity. An AI strategy can transform the way a company operates.”
ChatGPT is a tool, not a strategy
The ease with which ChatGPT can be accessed has made it much simpler to get started with artificial intelligence.
An employee can improve a text, create a summary or get help with research in a matter of minutes. This requires no complex IT infrastructure and often no in-depth technical training either.
However, it is precisely this simplicity that leads to a misunderstanding.
If ten employees use ChatGPT in ten different ways, the company does not yet have a common AI strategy.
It is merely using a tool.
A strategy only emerges once it has been defined how AI is to contribute to achieving the company’s objectives.
This involves, for example, questions such as:
- How can AI make our processes more efficient?
- Where can we reduce manual tasks?
- How can we make better use of existing data?
- Which customer processes can be improved?
- Which tasks can be automated?
- And which areas should we deliberately avoid changing with AI?
The key difference lies in the business case
She should start by addressing the problem.
For example, if a company spends several hours every day compiling information from various documents, AI could potentially deliver significant added value.
If, on the other hand, staff only carry out a task once a month, a complex AI solution may not make economic sense.
The business case is the deciding factor.
A sensible AI application should therefore generate a tangible benefit. This could take the form of, for example, time saved, lower costs, higher quality, faster decision-making or better customer experiences.
The crucial question is therefore not:
‘What can we do with AI?’
But rather:
‘Which specific problem can we solve more effectively with AI?’
The greatest potential often lies in the processes
Many companies are on the lookout for spectacular AI applications.
Yet the greatest potential often lies in less visible areas.
For example, a company may have numerous repetitive tasks in which staff copy, check, categorise or forward information.
Such processes are of particular interest.
When information is currently transferred manually between emails, Excel files, CRM systems and internal platforms, it is not just a waste of time. It also creates opportunities for errors.
AI, in conjunction with automation, can help to redesign such workflows.
The crucial step, however, is to analyse the entire process.
Not every single task needs to be replaced by AI. It often makes more sense to restructure the process and use AI only where it actually offers a benefit.
Data is the foundation of any serious AI strategy
Another point is often underestimated:
AI requires suitable information.
Companies today have vast amounts of data at their disposal. However, documents, contracts, customer information, emails, product information, internal guidelines and historical data are often scattered across different systems.
If information is not structured, up to date and accessible, it becomes more difficult to utilise AI.
That is why data management is an integral part of a serious AI strategy.
Companies must understand what information is available, where it is stored, who is authorised to access it, and how this information can be used for AI applications.
An AI strategy is therefore always also a strategy for data and knowledge.
AI without clear rules can create new risks
The more AI is integrated into business processes, the more important clear rules become.
Employees need to know what information they are permitted to enter into public AI systems and which data must be treated as confidential.
Issues relating to data protection, information security, access rights and internal accountability must also be taken into account.
This does not mean that companies should avoid AI.
It means that AI must be used in a controlled and deliberate manner.
A professional AI strategy therefore not only creates opportunities but also establishes a clear framework.
An AI strategy does not mean using as many tools as possible
The market for AI applications is growing rapidly.
There are now specialised tools for almost every task.
This is precisely why there is a risk that companies will end up with a confusing array of individual solutions.
One tool for text.
A tool for presentations.
Another for meetings.
Yet another for customer service.
And perhaps several AI applications for data analysis.
The problem is not the number of tools.
The problem is the lack of integration.
A strategic AI landscape should therefore be manageable, secure and meaningfully integrated into the existing digital infrastructure.
People remain a central component
A successful AI strategy does not mean automating as many tasks as possible.
People must continue to make decisions, monitor results and take responsibility.
Particularly when it comes to sensitive or business-critical issues, AI should be seen as a support tool rather than an uncontrolled decision-making authority.
The greatest added value often arises where human experience and artificial intelligence are combined.
AI can analyse large amounts of information and recognise patterns.
People can understand context, take responsibility and make decisions in the right context.
This combination can be significantly more effective than either approach on its own.
From using ChatGPT to a genuine AI strategy
The path to the strategic use of AI does not have to be complicated at the outset.
The first step is to understand the current situation.
Which AI tools are already in use?
Which staff members are using them?
For which tasks?
Which processes are particularly labour-intensive?
What data is available?
What security requirements are in place?
On this basis, organisations can identify and prioritise specific use cases.
Not ten projects at once.
But, to begin with, the applications with the greatest potential.
Successful solutions can then be gradually expanded and integrated into existing systems.
The approach of AM Consulting & Management
At AM Consulting & Management, we do not view artificial intelligence in isolation as a technology.
We bring together business strategy, processes, data, technology and people.
Together, we analyse where AI can actually create measurable added value within the organisation and what conditions are necessary for this.
The solution can take many different forms.
An internal AI knowledge platform.
Automated document processing.
Intelligent customer communication.
AI-supported processes.
A bespoke software solution.
Integration of existing systems.
Or, to begin with, a clearly defined pilot project.
The key is not to use as much AI as possible.
The key is to develop the right solution for the specific business problem.
Summary
Using ChatGPT is a good way to get started in the world of artificial intelligence.
However, an AI strategy goes much further.
It links business objectives with processes, data, technology and people. It defines specific use cases, takes risks into account and lays the foundations for integrating AI into the business in a meaningful way over the long term.
The difference can be summarised simply:
‘We use ChatGPT.’
means that a tool is being used.
‘We deploy AI strategically.’
means that technology is being used in a targeted manner to achieve specific business objectives.
At AM Consulting & Management, we support companies in taking precisely this step.
The crucial question is not whether your company uses AI, but whether your use of AI actually makes a difference.
Arrange a no-obligation AI potential analysis and find out where artificial intelligence can create tangible added value in your company.