Maximizing value creation with AI: A guide for CEOs
At a time when AI technologies, especially Generative AI (GenAI), are making rapid progress, the focus is on transforming potential into actual profit.
Is it possible to maximize profits by creating value with AI? With the right strategic approaches and innovations, you can actually increase the capital value.
In today’s digital era, artificial intelligence (AI) is at the center of many boardroom discussions. CEOs are increasingly asking themselves how they can get the most out of AI technologies and maximize business value. Our extensive experience in the implementation of artificial intelligence (AI) provides practical solutions and strategies that companies can use in 2024. These insights are supported by BCG studies based on over 1,000 client projects, as well as the Federal Ministry of Education and Research’s foresight.
Why now is the right time to invest in AI
The maturity of AI technology has reached a point where it is beyond the hype stage and delivers real added value. Generative AI (GenAI) in particular complements predictive AI and enables companies to operate more efficiently and innovatively in various areas. AI systems are becoming better and better trained and AI development is not only progressing through machine learning.
And so companies that have already taken AI measures are showing impressive results, such as 38% growth in EBIT over three years and thus achieving continuous profit maximization(BCG study).
The image shows the added value of AI in various areas of the company. It illustrates the reduction in agency costs in the commercial sector, efficiency gains for medical authors in research and development and accelerated reporting in marketing and sales.
Three strategic approaches to maximizing value through AI and increasing efficiency on top
Deploy (use of standard tools)
The goals are to increase productivity by 10-15%, improve employee satisfaction is always desired and prepare for more comprehensive AI implementations. For this, CFOs need to win as advocates of AI applications, a comprehensive AI strategy needs to be introduced or adapted. Good examples of implementation include meeting summaries, code development, calendar management, invoice reconciliation, automation, executive and management training and guidance. Internal workshops are very helpful here.
What AI software do you already use and where do you see the value of AI being maximized in your company?
Reshape (redesign of functions)
For redesign, the goals are to improve efficiency and effectiveness by 30-50% through workflow optimizations. A willingness to digitize and optimize technology must be achieved while always keeping AI ethics in mind. Perfect examples can be found in marketing, customer service, design and engineering as well as in communication.
In which areas of your company do you already use AI or are you even planning a reorganization?
Invent (inventing new business areas)
The aim here is to expand revenue sources through new offers, services and customer experiences. The increase in value is achieved through AI research and corresponding AI applications. A neural network is used here for machine learning. Examples include hyper-personalized customer experiences, AI-driven services, data monetization and data analysis using an AI application. The transformation of value creation and artificial intelligence in companies is forward-looking and essential for any company management. It is important to start with an AI workshop to evaluate the right use cases and low-hanging fruit. In addition, the team and people should be brought on board to make such projects work. At neuland.ai, we have found that the implementation of projects is up to 80% more efficient if the employees are correctly picked up in advance and properly involved. You can find more information about our Generative AI Executive Workshop and everything you need to know about interactive AI workshops here.
Which business areas do you see as potentially high?
This graphic shows the three strategic approaches to creating value with AI: Deploy, Reshape and Invent. Each approach has specific goals, such as increasing productivity, improving processes and developing new revenue models.
SuccessSuccess factors for the implementation of value creation with AI
To successfully scale AI and turn it into business success, companies need strong foundations: talent, technology infrastructure and a focused approach that concentrates 70% on people and processes, 20% on technology and data and 10% on algorithms. Maximizing value creation with AI brings a long-term competitive advantage and is achieved through data, talent and corporate culture.
This graphic illustrates the three pillars of value creation with AI. It shows that % of the focus is on people and processes, % on technology and data, and % on the development of algorithms.the transformation of value creation and artificial intelligence in the company are forward-looking.
Importance of a basic architecture
In a business world where AI applications are becoming the norm and employees in all areas of the organization – from purchasing and procurement to logistics, service management, call centers, etc. – are using AI assistants for a variety of tasks, a robust foundational architecture is essential. Organizations that have dozens, hundreds or even thousands of AI applications in use need a platform that provides speed, autonomy and secure results for users, while IT and management retain control over resources such as roles and rights, GPU usage, costs and data. Decision-makers should ensure that these requirements are met to prevent the creation of new AI silos and ensure efficient and coordinated use of AI technologies.
Imagine that you have developed numerous AI applications in parallel in the near future and then have to combine the costs, computing capacities and offers from different systems. This would end in total chaos. It is therefore of the utmost importance to establish a comprehensive and controlled architecture from the outset. This is the only way to ensure that all systems are smoothly integrated and that management always has an overview.
Employee involvement for effective AI solutions
Involving employees is crucial to developing the right AI solutions and implementing them efficiently. Employees are often the best experts for the specific requirements and challenges in their area of work. Through their active participation, realistic and practical solutions can be developed that increase the acceptance and success of AI initiatives. In addition, involving the workforce promotes a sense of participation and can increase the willingness to adapt to new technologies and processes.
Conclusion
In summary, it is essential that companies establish a solid AI architecture in order to effectively manage and optimize their AI initiatives. At the same time, employees should be closely involved in the development process in order to create practical and accepted solutions. These two aspects are essential in order to exploit the full potential of AI technologies and achieve sustainable business success. In addition, it is important to ensure continuous evaluation and adaptation of the AI models used in order to be able to react flexibly to changing market conditions and technological advances. The implementation of AI should not be seen as a one-off project, but as an ongoing process supported by strategic planning and targeted training of the workforce. Ultimately, an organization’s ability to foster integrated and data-driven decision making will be a key competitive advantage. By integrating these factors into their AI strategies, companies can not only increase operational efficiency and innovation, but also take a leading position in their industry.
