Deeper Insights Days: Success factor AI strategy: value-oriented into the future of market research

AI between hype and reality

However, the reality is different in most companies. The ChatGPT revolution has certainly set things in motion here: initiatives to further advance the digitalization of processes, new tools to automate lengthy processes and the availability of language models à la ChatGPT for internal use. At the same time, it is becoming increasingly clear that some problems are really difficult to solve, and even AI solutions and large language models do not simply make complex processes disappear. And many prototypes and proof-of-concepts remain at this level because scaling is difficult.

The big FOMO has also set things in motion in some companies. We have had many discussions with different departments over the past few months: There is great interest in solutions and use cases. This also goes hand in hand with the need for solutions that can be presented quickly, because after all, everything is very simple with AI: “You know, Mr. Harms, I quickly don’t care which use case we implement.” We have to show our management AI solutions that we use in our area. We have a meeting about this in two months.” Actually a great opportunity for us as an AI consultancy. But like any other project, implementation will be difficult without a clear vision, strategy and goals.

Clear AI strategies as the key to sustainable success

Please don’t get me wrong: I don’t want to deny that large language models – and what we will develop in the next few years – have huge potential. But we shouldn’t lose sight of what we actually want to achieve: answering questions about people’s needs, attitudes and opinions – and perhaps being optimally supported by technology.

In order to achieve the necessary clarity so that AI solutions can develop added value in the long term, we at the Skopos Group are convinced that AI strategies are needed. Be it by anchoring AI as part of the corporate strategy or by specialist departments formulating their own AI strategies. At the very beginning there are questions such as:

• Why do I actually want to use artificial intelligence? What do I hope to achieve from this?
• What goals do I want to achieve with this?
• How does artificial intelligence support/complement/replace me with my tasks and questions?
• What values ​​does our company/our department/our guild have that must be safeguarded?

The answers to these questions and the formulation of the strategy help to take the right direction in the ocean of possibilities. A good AI strategy includes numerous pillars:

• Objectives of the AI ​​strategy
• Identified use cases
• Data
• People & Skills
• Governance and ethics
• Infrastructure & tools

A well-formulated strategy should help me to concentrate on my core competencies as a market research institute or department and to invest time and money exactly where artificial intelligence can actually support me. These investments will pay off in the long term because the next prototype that was suggested to me on LinkedIn will not be ready after two months. In addition, it can be considered whether external service providers bring added value with tools and solutions and where specially developed approaches are superior due to the data or technical requirements.

Sustainable innovation through collaboration and training

That’s why we at the Skopos Group have formulated such an AI strategy since the beginning of this year: We want to use the opportunities of this technology in our projects where it is worthwhile for us and, above all, continue to do good work and support our customers through our expertise. Quality and advice inspire. As part of the strategy, for example, we have set up an “AI Embassy”, which serves for ongoing exchange between the teams and business units and combines different experiences in dealing with AI. Through an extensive training program on the basics and applications of AI, we want to enable all Skopos colleagues to use our tools carefully, know their new limits and advise our customers on all aspects of their use. Short-term quick wins are less important to us than long-term, effective solutions that we can continuously develop.

An example of this: coding of open information

The use case is as old as survey market research: We collect open answers from our respondents, the evaluation of which is significantly more complex than the quantitative data. At Skopos, too, we often rely on working students and employees for this purpose. Automated solutions have great leverage here to process projects faster and more cheaply. At the same time, quality plays an important role; ultimately, based on the results, communication materials are optimized, brand messages are reconsidered and customer experiences are conveyed to management circles.

Solutions have been around for a long time and a prototype can be set up quickly using GPT models. But in detail, the assignment is often a problem for very specific questions. We are therefore continually developing this solution and using our experience as market researchers and our expertise as an AI consultancy to achieve optimal results.

Our strategy also states that transparency and credibility are particularly important to us. What this means for our everyday life: The use of fully automated solutions is only possible in coordination with our clients and a human is always involved in important decisions and processes: Code plans are coordinated and always checked by a colleague and also the The final coding is (still) checked by humans, at least on a random basis.

At the Deeper Insights Day from planung&analyse we will present our AI strategy in detail and address specific use cases. Of course, what our clients can expect from it is also important.

Success with strategy instead of FOMO

Technological developments in recent years have been rapid and promise many changes. However, one thing should not be neglected: a critical look at what is available to us. ChatGPT is an excellent simulation of language and cognition – but still a long way from true intelligence. LinkedIn posts that promise the next big thing are aimed at investors and venture capital firms. However, this means that the AI ​​bubble continues to inflate because we lose sight of what added value this technology can actually bring us today and in a few years. Instead of blindly following the latest fashions, a moment of reflection can help to set the right course to keep the essential tasks and values ​​in mind and to benefit from the technological possibilities. An AI strategy can be a helpful tool to avoid succumbing to FOMO the next time you visit LinkedIn.