Partner POV | Ready or Not, AI Is Coming to Your Business

Article written by Martin T. Olsen, Vice President, Global Edge and Integrated Solutions, Vertiv.
 

Generative AI has changed the game

While artificial intelligence (AI) isn't new, the AI landscape changed dramatically with the release of ChatGPT in November 2022. That generative AI (GenAI) chatbot, the large language model (LLM) behind it and the subsequent releases have transformed AI from a tool only skilled technologists and data scientists were using to one anyone can access.

In the process, it sparked a technology revolution that, at the very least, will be as disruptive as the internet — and many believe much more so. Google CEO Sundar Pichai has claimed that AI will have a more profound effect on humanity "than electricity or fire," while Microsoft's Satya Nadella believes that GenAI represents the "first time a technology developed in Silicon Valley benefits the lives of everyday people so quickly and tangibly."

The business impact of GenAI

GenAI's emergence is expected to have an enormous impact on business across verticals. Goldman Sachs projects that GenAI has the potential to raise annual labor productivity by around 1.5 percentage points over a 10-year period and drive a rise in global GDP of 7 percent. 

McKinsey is equally optimistic. According to their research, GenAI could add the equivalent of $2.6 to $4.4 trillion annually across 63 use cases. The firm noted that this estimate would roughly double if they included GenAI use cases beyond those 63 analyzed.

As new GenAI use cases and tools continue to emerge at breakneck speed, here are some of the most interesting applications we've seen in finance, healthcare, government and manufacturing.

GenAI use cases in financial services and banking

The financial services industry is often quick to adopt technologies that can improve processes and services as small gains in speed or efficiency can yield large returns. Across the industry, GenAI is being evaluated or deployed in a variety of processes, from enhancing loan and credit risk assessment to managing regulatory compliance, detecting fraud and enhancing customer service.

For example, the newest iteration of the Visa Account Attack Intelligence (VAAI) Score uses GenAI to evaluate more than 180 risk attributes in milliseconds, generating a score that predicts the likelihood of a type of brute-force card attack aided by bots. The GenAI-powered VAAI Score has six times the fraud-detection features of previous models and has reduced the rate of false positives by 85 percent.

Financial firms are also seeing GenAI's potential to enhance customer service and decision-making. For example, Bank of America recently introduced an AI-powered virtual assistant, Erica, to offer personalized financial guidance to its customers. Capital One is taking a similar approach with Eno, an AI-powered natural language SMS assistant.

GenAI is also helping financial services companies navigate a complex regulatory landscape. Compliance management software providers are embedding GenAI and machine learning in their platforms to analyze regulatory rules, policies and processes, and to identify and assess compliance risks.

GenAI use cases in healthcare 

Healthcare has been one of the leading beneficiaries of GenAI, with use cases extending from pharmaceutical development to patient care. AI is being used to automate administrative tasks, enhance the analysis of medical images, assist in diagnosis, and develop personalized care programs.

One of the most exciting use cases is drug discovery and testing, where GenAI can accelerate the process of identifying compounds for new drugs and speed their development. A study by the Boston Consulting Group found that GenAI can reduce the cost and time of drug development and testing by 25 to 50 percent, enabling life-saving and life-changing drugs to get to market faster. Here are a few examples:

• Researchers at MIT used AI to screen more than 100 million chemical compounds, leading to the development of Halicin, an antibiotic that has been found to be effective against many drug-resistant bacterial strains.
• Insilico used its AI platform to generate and optimize INS018_055, which is designed to treat idiopathic pulmonary fibrosis (IPF), a form of lung disease. Now in clinical trials, the drug was developed in just 18 months from target identification to preclinical candidate nomination.
• Biotech company Recursion has used AI on biological image data to identify more than 20 new drugs for investigational work into genetic- and age-related diseases, several of which are now in clinical trials.

GenAI use cases in government

Governments and public sector entities may end up being the largest users of GenAI due to the large constituencies they serve and the massive amounts of data processed daily.

Within the U.S. federal government, use cases for GenAI were emerging so quickly a database had to be created to track them all. That database now includes more than 700 examples of how departments and agencies are using AI, Examples include analyzing urban heat islands, protecting residents against extreme weather, analyzing non-structured feedback from military veterans to improve service delivery, and accelerating the process of comparing new patent applications to existing patents.

In Argentina, the Ministry of Health is using GenAI to predict the spread of diseases like dengue fever based on climate data and population movements. Locally, the Public Prosecutor's Office of Buenos Aires worked with the University of Buenos Aires AI Lab to develop Prometea, an AI virtual assistant designed to expedite this work.

GenAI use cases in manufacturing 

Manufacturing has already greatly benefitted from AI and other advanced technologies, and GenAI will only enable even more efficiencies and quality. AI is being used within the sector to accelerate product design and development, monitor quality, and increase the accuracy of production planning and inventory management. 

General Motors (GM) uses generative design powered by AI to drive continuous improvement in vehicle components, with a focus on lightweighting. Collaborating with AutoDesk, GM engineers were able to quickly evaluate more than 150 alternate designs for a seat bracket, landing on a simplified design that reduced weight by 40 percent and increased strength by 20 percent.

Airbus had a similar experience with generative design, using it to create a stronger, lighter-weight partition for the A320. They used GenAI algorithms based on natural growth patterns to optimize the partition's structure. The resulting "bionic partition" is 45 percent lighter than traditional designs while meeting strict requirements for stress and crash force displacement.

In the plant, GenAI is being used to increase manufacturing uptime and reduce service costs. AI models can be trained on data from equipment sensors and learn to recognize patterns from equipment data that may indicate impending failure. AI is also being used to analyze historical maintenance data to aid in troubleshooting and failure analysis.

Preparing for the AI and digital revolution

The question isn't if AI will come to your business but when — if it isn't already there. As you get excited about GenAI's potential impact on your organization, it's important to identify a strategic roadmap for AI transformation that maximizes the business value of your AI investments and use cases.