- IMD Business School
Digital transformation

Generative AI: What is it, and how can it impact business?

The artificial intelligence (AI) realm saw a significant stir towards the close of 2022, as OpenAI unleashed ChatGPT to the digital world, promptly amassing an impressive 100 million users in just a few months. The driving force behind this remarkable uptake? Generative AI models, designed to mirror human thought processes, producing output derived from their intensive training data.

But the question that now presents itself is: How can businesses effectively utilize generative AI to enhance their outcomes?

This comprehensive guide takes you on a deep dive into the multifaceted impact of generative AI on business, highlighting the potential benefits and pitfalls. We’ll shed light on the pros and cons of AI, unraveling the complexities and challenges of its application within the professional sphere.

  1. What is generative AI technology?
  2. What are some examples of generative AI?
  3. How can generative AI helps business grow?
  4. What are the challenges that come with using generative AI?
  5. How to revolutionize business with generative AI?

What is generative AI technology?

Generative artificial intelligence is a branch of AI that uses machine learning models to take user input and output different media formats in response to what the user gives it. It takes training data from data scientists and learns to identify patterns based on what it has learned.

Although much of the excitement about generative AI in real applications has happened recently, it’s been around for a while. It was initially conceived in the 1960s with the first generative AI chatbot, Eliza. The most recent trend of generative AI started in 2018 when Google released its Transformers paper. Transformers were a new form of neural networks and deep learning that formed the basis of many AI technologies today.

Since then, researchers have used Transformers in combination with what they already know about how AI works to create new AI models that are better than anything before. AI can now create text, images, audio, and video using both commercial and open-source AI models.

What are some examples of generative AI?

Generative AI models have made many advancements in recent years, with use cases in several industries. Here are a few notable examples.

  • Content creation: This is one of the most popular uses of generative AI. You can train AI models on the data you want them to learn and have the AI models output content based on their training data. AI can output new content using text, images, and other media based on your input.
  • Chatbots and virtual assistants: Written content creation is fast and easy with chatbots and virtual assistants. Businesses can feed proprietary information to large language models (LLMs) to get text-based answers.
  • Image generation: Image generators like Midjourney, Stable Diffusion, and DALL-E allow users to create AI images just by typing in a prompt of a few words. They can create anything from fantasy landscapes to realistic-looking photos.
  • Healthcare: Generative AI can also speed up certain healthcare industry processes. It can generate synthetic data to help with drug research; These can include generated images that can supplement real patient data and serve as additional training data for AI models. 
  • Social media: Generative AI allows social media platforms to serve users better by offering personalized content. There are also new social media tools for business owners that allow them to create AI-generated content for social media ads using automated tools.

How can generative AI helps business grow?

Generative AI tools have a lot of useful applications, but how can those applications help organizations? Here are some of the most beneficial ways that AI solutions can optimize your workflows:

Enhancing productivity and efficiency

Generative AI systems allow workers to get more done by automating processes that require workers to create.

For instance, you can use AI tools to write emails, draft proposals, summarize text, and write programming code. These tools are great if you’re stuck trying to come up with something to write. AI can also generate data that’s useful for analysis-related tasks, speeding up data-driven decision-making.

Improving customer experience

Generative AI offers many tools to help you serve your customers better. Among those tools, chatbots offer some of the best value.

Chatbot programs can fine-tune a language model from a foundational model. It uses your company’s information to learn what features it has and the problems customers face. This means a chatbot can converse intelligently with customers using natural language processing (NLP) and help them solve problems, leading to less time waiting for a human agent to get help.

Generative AI can also help streamline other parts of the customer experience. Take, for example, a customer who isn’t sure what they want. If you have certain data about that customer, like past purchases or demographic information, generative AI can help you use it to create an experience that helps them find the perfect product for their needs.

Reducing costs

One of the least necessary costs of a business today is time spent on manual tasks. Every minute your team spends on tasks you can automate – like data entry and information summarization – is money you can use elsewhere.

You can use generative AI to automate many of these tasks, eliminating some of the labor and saving you money. It will also help you minimize errors (some of which can be costly) and reduce the need for manual intervention.

Generative AI is also useful for minimizing other operational costs. You can use it to generate different business scenarios to find the one that’s most efficient.

Keeping you competitive

The AI race isn’t likely to slow down. According to Accenture, 90% of business leaders use AI to tackle different parts of their businesses. And as AI becomes more accessible, small businesses can increasingly use it, too.

Generative AI models can help you analyze the market, brainstorm solutions to new problems, and offer something great to your customers and stakeholders. AI models like GPT-3 and GPT-4 can surface new ideas you may not have thought of otherwise, including new solutions and ideas that can give you an edge.

What are the challenges that come with using generative AI?

Generative AI tools offer many benefits, but there are also challenges to generative AI that you must consider. Here are some of the major risks organizations face in using this technology:

  • Ethical concerns: The information generative AI produces isn’t always accurate, and can even produce deepfakes (visuals and audio that give the impression of someone doing something they didn’t actually do). Using AI means understanding these concerns and using AI ethically.
  • Intellectual property concerns: A major concern people have had with generative AI is the datasets used to train it. Nobody has a list of everything the current AI models use for training, which means the chances are good that it included copyrighted material. This can lead to AI reproducing intellectual property without the owner’s consent.
  • Biased data: AI models are only as good as the data you train them with, and much of that data comes from humans. The problem with that is human bias, which can show up in AI output. You’ll need to find a way to find and address these biases to improve your AI’s reliability.
  • Good input prompts: The right input prompts are key to using generative AI optimally. You need to tell the AI tool precisely what you want and give it the resources to create great output – a process called prompt engineering. It will take experimentation to learn how to prompt well and use your prompts to constrain your AI’s output to what you need.
  • Security concerns: Security is an especially big concern to address if you use a third-party cloud service. Some organizations have sensitive information and can’t afford to let that data leak because of an AI vendor. Consider security issues like these before using AI.

How to revolutionize business with generative AI?

Generative AI has made considerable strides in the recent past, marking its position as one of the most prominent technologies in the AI landscape. From amplifying creative capabilities to facilitating superior product and service offerings, generative AI promises a wealth of opportunities.

However, as the technology continues to evolve, so do its benefits and associated risks. Therefore, understanding how to leverage AI ethically and safely is essential to maintain customer trust and stay competitive.

Embarking on an AI journey may appear daunting, but you need not navigate it alone. IMD’s Digital Strategy, Analytics, and AI program is designed to provide the knowledge and confidence you need to integrate AI into your organization effectively.