Artificial Intelligence (AI) in energy sector
Companies need to look at the topic from a strategic perspective and systematically identify elements in their value creation that can be evolved and benefit from AI. AI has potential uses in all areas of the energy sector: production, sales, trading, maintenance, and the development of new service offerings and products. Examples of applications include grid control centers of the future, control and management of decentralized electricity storage, more reliable and long-term forecasting models, reduction of energy peaks, and the design of sales and trading platforms. By automating processes and using AI, competencies can be shifted and strategically developed within the company.
The energy sector faces several challenges:
- Demographic change: Long-term employees retire after 20 to 30 years. New employees stay significantly shorter periods of time.
- Growing complexity: Energy systems of the future are becoming increasingly complex and interconnected (decentralized power production [wind, PV], electromobility, consumption communities, local battery storage, etc.).
- Cost pressure: The infrastructure deployed is capital-intensive, and there is a need for action independently of the market liberalization that has been discussed for years.
Changes in the energy market will increase in the coming years, and companies must proactively deal with them and ensure that they remain competitive. This is not just about ensuring the security of supply but also about long-term business success.
AI is not science fiction, but a radical form of automation
As a branch of computer science, artificial intelligence deals with automating intelligent behavior and machine learning.
The concept of AI relates to data and data models as well as learning models based on them. With increasing amounts of data, patterns and regularities in learning systems can be better identified on an ongoing basis and serve as the foundation for new solutions. Complex tasks are solved in a safer, faster, and cheaper way. The range of services is expanded, value creation is automated, the quality of the service is improved, and efficiency is increased.
Challenges in implementation
- AI and the new models require a lot of action and a corresponding willingness to change. The corporate culture often lacks internal “entrepreneurship” to address opportunities profitably. The necessary changes go far beyond incremental changes.
- Relevant competencies for the implementation and application of AI must be built up systematically in the companies.
- Used incorrectly, AI increases complexity instead of reducing it. AI is not yet “plug and play”.
- Topics such as data privacy and ownership are often perceived as a hurdle. The company’s position on this must be clearly addressed so that future developments are not cut off early.
The holistic corporate design clearly shows the need for innovation and enables a coherent strategy
Companies need a holistic solution approach for the implementation of AI. The hpo approach has proven its viability in incorporating new technologies and methods for years.
- Assessment and evaluation of the initial situation. Systematic analysis of the value chain and the organisation regarding specific potentials of AI.
- Clarification of market positioning using a precise industry model as the basis for strategy, including business process model and organisation.
- Identification of customer-relevant interrelationships and dependencies using an innovation architecture and its differentiating elements.
- Deriving measures and identifying the right combination of innovation activities. Ensuring the implementation and adaptation of processes, leadership and corporate culture to increase competitiveness.
Innovation must be considered as an integral part of the strategy for companies to maintain and expand their competitiveness in the long term. All activities in the company must be aligned based on their value contribution to the customer. Governance, data protection, and compliance must be ensured intrinsically. Companies create the basis of a learning organisation by systematically operationalizing new products and business models, anchoring them in the organisation, and monitoring their strategic and operational impact.
AI holds exciting potential, and it is a matter of time before the “revolution” shows its first effects in business. Companies need a systematic approach to achieve value through AI in a resource-efficient way. This does not require short-term brainstorming sessions but a deep and long-term understanding of upcoming industry changes and market performance architecture towards existing and new customers.
hpo helps companies navigate their way into the future and thus creates the prerequisites for high-performance organisations of tomorrow. Contact us directly for a non-binding consultation.
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Who is hpo?
hpo makes companies more successful and more innovative. The strategy consultancy for enterprise design boasts more than 25 years of experience in the creation of strategies and organisations spanning many different industries. The management consultants at hpo specialise in the meticulous development of strategies, processes, business models, innovation and culture, and in accompanying the transformation.
The hpo design approach enables companies to better cope with strategic and organisational challenges and to realise substantial competitive advantages. The basis of the industry-spanning design approach is an academically grounded methodology with which high performance organisations are shaped and which is continually further developed with the latest findings from research and practice.
The management consultants at hpo come from a commercial or technology background and stand out with their high level of analytical and emotional intelligence. They are passionate in their dedication to the client’s concerns and enjoy working in a team.
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