Data-driven innovation and new skills Above all, the role of experts in product development has changed fundamentally. However, the use of this new type of communication interface requires very differentiated skills when formulating questions, especially as the unique context of each company must be taken into account. de Companies are therefore required to focus on knowledge management, process optimization and the redesign of business models. This is the only way to achieve extensive automation of development processes and give creative teams the space they need to generate the necessary momentum. At the same time, companies must face up to the ethical implications of AI innovations and find responsible solutions.
They are the ones who have to find a balance between innovation and regulation. A recent study by the European Central Bank, for example, assumes that AI will have a predominantly positive impact on employment - especially in countries with rapid AI introduction and good education. At the same time, companies must also address aspects such as confidentiality, security, sovereignty and environmental impact, particularly in the context of ESG requirements (ESG - Environment, Social, Governance).
AI versus sustainability - a balancing act for CIOs And another balancing act for CIOs is just around the corner: according to Sajjad Moazeni, Assistant Professor of Electrical & Computer Engineering (ECE) at the University of Washington, ChatGPT, for example, receives hundreds of millions of queries every day. The energy consumption of the infrastructure associated with this quantity amounts to around one gigawatt hour per day. It will therefore be crucial to be able to justify the use of AI through cost and CO2 savings elsewhere. Together, they form an AI platform on which companies can train and operate their models. The necessary choice between open and closed AI models as well as specialized applications plays a decisive role in the strategic decision-making process of companies. This is because the individual models sometimes differ significantly in terms of security, costs and implementation complexity. This also plays a particularly important role in the scaling of services.
Faster deployment and productivity through AI governance
As AI is driving exponential change, companies and CIOs cannot do without effective AI governance. Above all, it should continuously recognize and evaluate new opportunities, technologies and applications. At present, it is primarily generative AI that is undergoing a multi-stage maturation process, with the current focus on knowledge management and functional process optimization. The next phase, which focuses on the redesign of products and offerings, will gain momentum in 2024. This represents a major challenge, especially for larger, established companies, opening up markets for many start-ups that are establishing themselves as specialist providers of AI products and services.
Ethical and copyright issues
When acquiring AI base models, CIOs need to clarify many ethical and copyright issues, for example by carefully reviewing and understanding license agreements. Questions about derivative works, data used in training and the copyright status of model outputs also need to be clarified to ensure responsible and legal use. This holistic approach ensures above all a secure AI (especially in terms of preventing user violations and unauthorized access), but also a responsible AI (implementing ethical standards against bias and for transparency) and a self-financing AI that is economically viable and cost-optimized.
The market for IT and AI service providers IT and AI service providers are rated better by users if they also have an extensive (global) presence and expertise in terms of consulting. In the ''Star of Excellence Voice of Customer'' study by the Information Services Group (ISG), providers with comprehensive consulting capabilities received higher customer ratings (87.4 out of 100 points on average) than those providers that ''only'' focus on technology implementation (82.6) or business processes (78.9).
Information in this article was originally posted by: CIO