Human intelligence is Needed to Deal with Artificial Intelligence
Digitalisation, and artificial intelligence (AI) and robotics in particular, deliver new technologies and solutions on an almost daily basis. At the same time, however, the pioneering Green New Deal, the Corporate Sustainability Reporting Directive (CSRD), the Supply Chain Act and the AI Act, for example, are presenting companies with growing challenges: The regulatory requirements for sustainable business are increasing sharply.
Many companies are so preoccupied with the bureaucratic requirements and the ‘pain’ that they often lose sight of the actual ‘gain’ – the positive sense and benefits behind the regulations.
AI can help to collect and analyse huge amounts of data, but data alone is not enough. To turn this ‘cold’ data into real, ‘warm’ data that really helps decision-makers, you need people who can interpret and process this data and put it into the right context. This is the only way to make well-founded decisions that not only focus on short-term solutions, but also support change in the long term.
In these dynamic times, in which long-term planning often fails in the face of reality, the ability to adapt quickly is crucial.
AI can provide support here, but the decisive factor remains people – with their ability to use data sensibly and translate it into action.
The Real Challenges Lie Within the Organisation
As a recent study by Boston Consulting shows, 85 per cent of system conversions fail not because of the technology, but because of the organisation.
Culture, mindset and the ability to break old patterns are the real construction sites.
Many companies are not like Nike, where “the only constant is change” is the order of the day. Instead, they struggle with rigid structures, a lack of necessary skills at many levels and resistance from relevant stakeholders.
Successful change requires not only technological innovation, but also a profound change in the way people work together. New skills are required: from data expertise and agile working to a culture that not only accepts change, but actively drives it forward.
Pattern Change: Real Transformation Instead of Mere Optimisation
In many companies, the focus of change is often on optimising existing processes. This means that existing processes are simply made faster, more efficient or more cost-effective.
But true transformation goes beyond optimisation. It requires a fundamental change in ways of thinking and acting, i.e. ‘doing things differently’ and not just ‘doing things the same way’ at a faster pace.
True transformation means creating new patterns – patterns that focus not just on speed and efficiency, but on approaching things in a fundamentally different way. This requires courage to let go of old, often deeply rooted structures and make room for innovation. This is precisely where Christensen’s innovator’s dilemma comes into play: companies that focus on optimising existing processes run the risk of missing out on disruptive changes. They remain trapped in their old models of success and fail to radically realign themselves.
Transformation therefore requires not only new technologies, but also the willingness to question traditional success factors and break new ground.
The Path to the Future: AI as a Catalyst, but not the Only Solution
The future of companies depends on how well they master this transformation. AI can be a powerful tool for making the right decisions in an increasingly complex world. But in the end, it’s people and org design that make the difference.
A successful transformation requires an organisation that is flexible, capable of learning and courageous enough to constantly reinvent itself.
How can this work? We discussed this at our AI Impulse Breakfast on 20 September at Tabaktrafik in Linz. Among other things, we highlighted the following use cases:
Location analysis: How can AI benefit our industry and where do we stand both technically and organisationally?
In order to successfully drive forward the digital transformation, it is crucial to know the current status of the organisation at both a technical and organisational level. A location analysis that shows the benefits of AI in your industry helps here. We will present a method for determining the current situation that will enable you to define clear guidelines for action. This allows you to take targeted measures to increase the maturity of your digital transformation and plan concrete next steps.
Creating learning organisations: How can AI and design thinking be used to foster a desire to learn and develop the organisation?
In a constantly changing world, companies not only have to react to the market, but also understand it. AI and design thinking offer valuable methods for anchoring this ability to learn in the organisation. Formats such as promptathons and hackathons, which involve large parts of the workforce and relevant stakeholders, can be used to think about the market and at the same time promote the joy of learning. The aim is to create a learning organisation that not only reacts to change, but also continuously develops and proactively shapes the market.
Transformation in the breath of the new: How do we design transformations in such a way that they already integrate the new ways of working that will be necessary in the future?
If more agile structures, end-to-end responsibilities or more decentralised decision-making processes are required in the future, the transformation process must already embody these new ways of working. This means that during the transformation, work is already being carried out in the way that will be required in the future: Faster, less linear and cross-departmental. Instead of going through traditional structures, agile, flexible teams are already being formed during the transformation, reacting to changes in real time and thus anticipating future ways of working.
Together with Albert – Ortig co-founder of Nxai – we addressed these topics and developed practical solutions. Our AI Impulse Breakfast not only provided insights, but also concrete approaches to successfully master the challenges of the future.
Literatur:
Clayton M. Christensen (1997): “The Innovator’s dilemma”
Pidun, U., Reeves, M & Schüssler, M (2020): “Why do most business ecosystems fail”
Dr. Weßels, D. & Haas, O.: ZOE 3/24: “Immer schön auf Sicht fahren – ein Gespräch über die Zurückhaltung deutscher Führungskräfte im Umgang mit KI“
Wintersteiger, C. (2020): Case Story Daikin – Transformation mit Org Design
