Generative artificial intelligence (AI) is perhaps the most tantalizing frontier in technological innovation. The advancing technology has spawned increasingly realistic synthetic imagery, from works of generative art to complex data analysis by computers learning to create near-photorealistic images and tell stories with surprising depth and clarity. These algorithms could easily pass as human creations, moving AI’s capabilities beyond crunching data and insights to creating data and insights that weren’t there before.
At the heart of all the excitement, however, are concerns about unintended consequences and the potential for abuse and misuse. These are artfully constructed narratives and striking images, but there’s also an undercurrent of cautionary notes. Still, AI has the power to transform business and society for the better.
AI’s Impact on Business
When harnessed correctly, generative AI can help companies innovate quickly, reduce costs, produce more revenue, improve efficiency, and enhance customer experiences. That’s because unlike traditional AI, which can only perform preset tasks based on the specific data and rules used to train its algorithms, generative AI features a component of creativity. It can make decisions or solve problems based on the patterns and structures it learns from the vast amount of data it receives, thanks to its usage of deep learning models. Generative AI can also produce incredibly realistic content, offering everything from text and music to audio and images. Among the models that can perform these functions are ChatGPT, which can create brand-new content, and DALL-E, a text-to-image model that creates digital images from prompts.
The adoption of generative AI has been swift. According to a June 2023 BCG survey, 70 percent of marketing companies have embraced generative AI, and a 2023 Harris poll found that 69 percent of U.S. hiring managers use generative AI, with 52 percent using it primarily for processing data for customers, operations, and employees.
Strategies for Success
While companies don’t want to lose their competitive edge by not embracing generative AI, they risk failure if they don’t adequately prepare and implement the technology correctly. Although a pervasive trend is for companies to follow the model of fail fast and fail forward, a long-term sustainable business model is required to be successful. Angela Zutavern, partner and managing director at global management consulting firm AlixPartners, says, “Experimentation is critical for any AI-generated initiative because not all of them will work the first time. But initiatives must be goal-oriented. If you expect a particular AI initiative to reduce customer churn or increase customer lifetime value, for example, you’ve got to be measuring that along the way.”
For these reasons, it’s important to keep milestones short-term and to consistently monitor, evaluate, and measure. For example, when onboarding a generative AI service, it’s essential for companies to first identify a champion to spearhead its implementation in a specific use case. This initiative can be monitored for a couple of months before moving on to the next milestone, such as providing access to a pilot team, educating them about the ethical guidelines, and ensuring they follow them. Once successfully launched in one area, ask the question, “How can it be disbursed to different teams?” It’s also beneficial for companies to consider bringing on a skilled policymaker to show those involved how to use the model effectively and train teams on handling sensitive data and the ethical issues surrounding generative AI.
Investment Considerations
Deciding what type of generative AI service to use is crucial. How significant are the security risks and financial constraints? Does it make more business and financial sense for the organization to use an in-service provider environment or have its generative AI created on-premises by installing the software at the company’s physical location instead of in the cloud or at a server farm?
There’s also no point in investing in AI if companies are unwilling to invest in reskilling and upskilling their employees. According to a 2023 Gartner survey, 79 percent of functional leaders will begin or continue implementing generative AI over the next 12 months. “When you introduce AI into the way people are working, there’s an immediate need for learning the new ways of working,” says Helen Poitevin, VP analyst at Gartner’s human resources practice. Regarding the real concerns of lost jobs, Poitevin says employers can shift from “thinking about what jobs will go away” to thinking about the work that needs to be done.
Avoiding Pitfalls
Companies can make better decisions about their adoption of the technology by remembering generative AI is currently unevenly distributed. The biggest players today are Google, Microsoft, and Amazon Web Services. As economically powerful organizations, they invest in creating generative AI services and base models for the rest of the world.
Unfortunately, the average-size company can’t afford to invest in large models such as Microsoft Azure. It’s not just small companies that should consider their investments carefully. In 2017, MD Anderson Cancer Center put its project with IBM Watson for Oncology on hold after it spent $62 million without achieving its goals.
To create a strong, safe AI platform, companies can focus on their internal frameworks as government regulations continue to expand. That includes ensuring transparency to understand how their generative AI algorithms make decisions and that their data is valid, ethical, bias-free, and as robust as possible to withstand cyberattacks.
Ethical Concerns
Ethical concerns are some of the most consequential issues facing the adoption of generative AI. With so much data being collected, analyzed, and utilized, potential problems include abusive behavior from chatbots, bias and discrimination, issues of deepfakes that create highly convincing false images, videos, or audio, and cybersecurity attacks.
In 2016, Microsoft launched its Tay Twitter chatbot, designed to speak like a teenager. Within 24 hours, the bot began sending out offensive, racist tweets. In July 2023, Florida Governor Ron DeSantis used an AI-generated voice that sounded like former President Donald Trump to attack Trump himself in a political ad. In February, explicit AI-generated photographs of pop star Taylor Swift were released on the internet. The Washington Post reported that AI-generated explicit photos have increased more than 290 percent since 2018 on the top 10 websites that host these types of photos.
Company executives view cybersecurity attacks as the top threat, exacerbated by generative AI. In 2023, there were more than 2,300 breaches in the United States. “It’s important for companies to look for these next-generation technologies to identify and prevent attacks using things like AI,” said George Kurtz, CEO of CrowdStrike, a company that monitors businesses’ systems to ward off cyberattacks.
Looking to the Future
Although companies will have to navigate ethical and regulatory hurdles, the future of generative AI is bright, with the ability to have incredibly positive impacts on a variety of industries. According to TechTarget, some of the greatest (and most rapid) gains will be seen in education, healthcare, and finance. Generative AI can tailor curricula for students based on their individual needs and specific learning styles. In healthcare, it is expected to improve patient outcomes through accelerated drug discovery, enhanced accuracy of diagnoses, and more efficient clinical operations. In finance, it will optimize engagement with customers, particularly when it comes to credit score monitoring, fraud detection, and financial planning,
There is much to be excited about when it comes to embracing generative AI, as long as companies recognize it’s not just about the machines. Rather, effectively leveraging technology centers on finding the precise balance between people and technology and taking small, achievable steps to reach their goals. Companies that understand this will take the steps needed to keep up to date with the ever-changing ethical and regulatory guidelines, ensure they have robust security systems, and adopt a policy of continuous learning. When businesses adopt a strategic and holistic approach to generative AI, it can transform their day-to-day operations and enhance their bottom lines.
