Report Presents Current Use Cases and Election Risks of Utilizing GenAI

This article was originally published on GT Perspectives.

"Since OpenAI (US) launched ChatGPT in November 2022, AI, especially generative AI, has been driving investment for corporate entities," According to a white paper published by The Economist Intelligence Unit (EIU). "Nvidia, Microsoft and Apple (all US) have all been racing to be the most valuable companies in the world, with Nvidia leveraging its chips, Microsoft its cloud, and Apple its iPhone and other hardware. They are all looking to create a compelling ecosystem, even though this may put them even further in the crosshairs of regulators." The report crucially asks: "is progress in AI moving the technology from an experimentation to an implementation phase?"

The report looks "at how companies have been using generative AI to date, and whether AI-generated content has had a major impact on elections so far in 2024." Key findings include:

• The launch of ChatGPT and similar services has democratized the use of artificial intelligence (AI) in many industries, and companies are now experimenting with and implementing the technology.
• The main use cases so far for generative AI have been to improve operational efficiency, enhance innovation and support customer service through using chatbots.
• Most businesses still rely on non-generative AI, however, and it remains important for them to understand the limitations of generative AI technology, such as hallucinations.
• The biggest impact in the short term will be felt during democratic elections, particularly in countries with a polarized electorate, a fragmented information ecosystem and global influence (including the US).
• As AI implementation continues, sustainability will become a major barrier, given that generative AI systems use a lot of electricity and have a large carbon footprint.

Addressing how companies are using generative AI, the report points out:

Companies in multiple industries have been experimenting with generative AI. Although the technology is new, two of the three major use cases across sectors are typical of many digital transformation strategies. The first is to improve operational efficiency, either in terms of increasing productivity or improving manufacturing and operational processes, often to cut costs. In the tech sector, this often includes using AI to speed up coding, or it can optimize internal processes such as training. Companies are also looking at technology to drive new revenue streams: generative AI is driving innovation across multiple sectors such as energy, financial services or healthcare, for example by making it easier to digest and analyze research papers. It is also used in customer services or to create better client-facing customer experiences. As the technology runs on large language models and is capable of dealing with vast amounts of text (as well as other media such as images), this is an area where development will continue across several industries, not just to interact with customers, but also for marketing purposes.

The EIU provides examples on how companies in certain sectors are using generative AI to drive innovation, efficiency and improve customer service:

• Automotive: (1) In-vehicle voice assistants and (2) chatbots to facilitate sales leads online
• Consumer Goods: (1) Creating custom products, (2) voice/text enabled customer service assistants, and (3) inventory management
• Energy: (1) Aiding oil and gas delivery and (2) customer apps to optimize energy demand
• Financial services: (1) Insurers use it for underwriting, (2) custom GPT based on internal data for advisors, and (3) cashflow management
• Healthcare: (1) Drug development, (2) custom GPT-based database to help with research and development, and (3) chatbot for public healthcare

Regarding how AI-generated content can have an impact on elections, the report notes: "Generative AI is not only being integrated into the corporate world; it is also infiltrating the political world. With 2024 being a year of multiple elections, and more than 4bn people called to vote, the impact of AI-generated content (both legitimate and fake) in election campaigns is only just emerging and will only increase."

As for sustainability becoming a major barrier to AI adoption, the EIU explains that "AI will continue to be implemented in 2025, but we expect that the main focus will be on sustainability. The 2024 Electricity report from the International Energy Agency (IEA) noted that global electricity demand from data centers, driven by AI usage, could double between 2022 and 2026, adding to the grid the equivalent of Germany's national consumption. Regulators are already looking into the issue."

Moreover, "In the US, the Artificial Intelligence Environmental Impacts Act of 2024 was proposed in March 2024 to assess and mitigate the environmental impact of AI; however, it is unlikely to become law before the November 2024 elections. The EU is further ahead, with the European Commission adopting the Energy Efficiency Directive (EED) in March 2024, which Germany has already implemented into law. From September 2024 data center operators will be required to report on areas such as data volume, renewable usage or waste utilization to reduce energy consumption and carbon emissions."

I support the EIU's conclusion that "The implementation and evolution of AI will be an ever ongoing process. The technology needs to be scaled up, and proponents need to move away from overoptimistic forecasts of artificial general intelligence (AGI) happening before the end of the decade. AI does not need to be perfect to have an impact. In fact, everyone should be aware that it is not perfect, and its usage will depend on the use case and require critical human oversight."

How is your business utilizing AI?

Aaron Rose is a board member, corporate advisor, and co-founder of great companies. He also serves as the editor of GT Perspectives, an online forum focused on turning perspective into opportunity.