Unleashing the Power of AI: Transforming Your Business for Success

You can’t watch the news, have a discussion at the company watercooler, or browse articles online without hearing some talk on AI (artificial intelligence). What is AI? A basic definition is machines perceiving, synthesizing, and inferring information. Much of the discussions centered around AI these days is focused on generative AI, which outputs information in a way that feels convincingly human. One reason for all the increased chatter about AI is the quality of output from these platforms. What once felt clunky now feels much more real.

As AI becomes more intelligent and its outputs become more human, organizations need to carefully consider whether implementing AI into their business strategies makes sense. To understand this conundrum a little more, let’s talk about what you need to know when making this decision, including how AI works, what it can do, the challenges you may face as you consider AI, and some steps to take when implementing.

What Can Generative AI Do?

Today, generative AI can do many things, including the following:

Generate code or open text
Generate images
Generate music

Organizations are using AI to generate code for website designs, compile images for marketing, write music for reels, and create copy for content purposes. Some popular generative AI options include ChatGPT, Gemini, Midjourney, Stable Diffusion, and MusicLM. These tools are improving efficiency and driving creativity in business, with 89 percent of employees saying that implementing one of these tools can improve their workload.

How Does Generative AI Work?

Understanding how AI works is imperative to understand how to leverage it within your business. At its core, AI platforms are complex statistical models designed to predict what’s next. For instance, if you input a prompt into ChatGPT that says, “Finish the sentence ‘I like to eat,’” the response generated might be “I like to eat a variety of cuisines from around the world.” The platform predicts what it thinks you might want the response to look like.

What makes AI so powerful is that it has access to incredible amounts of information. It is estimated that the training data for platforms like ChatGPT have billions to trillions of words in their database (about 570 GB). They also have incredible computational power, allowing AI to get smarter and make better suggestions. With ongoing human feedback, these platforms are constantly refining their models, implementing rules to help block harmful responses, and improving responses that better match input requests.

What Are the Challenges of AI?

AI seems very shiny and new and can be very enticing to businesses looking to improve efficiency, drive creativity, or enhance their competitive edge. However, AI comes with a unique set of challenges that you need to understand before moving forward.

Hallucinations. These are AI-generated responses that are untrue or misleading, such as a ChatGPT response that indicates you gave a TedTalk or have been quoted in the New York Times. AI models are often compared to an incredibly eager intern who doesn’t know how to say, “I don’t know.” This means a human must review outputs to ensure the authenticity and accuracy of information.
Bias. Because the data in AI is trained, societal biases can be built into the data. Again, the human eye is required to remove any bias in outputs.
Data Governance. One of the most worrisome things about AI is what is done with the information we put into the software. While inputting our favorite breakfast dishes might not require privacy protection, sensitive customer data does. Understanding how our data is stored and used needs to be more clearly understood.
Computing Power. Smaller startup AI platforms will have less computing power and less capital to improve training of their AI. This can cause issues with incorrect outputs and problematic data. Consider this when choosing an AI tool for your business.
Unknown Future Costs. Currently, most AI platforms are offering their software at low prices, but because of the capital required to generate information, those costs may skyrocket at some point. Who will bear the burden of those costs in the future? We don’t yet know.

These challenges should not deter you from embracing AI but rather help you make a more informed choice about which AI may work for your organizational goals. Let’s take a closer look at some of the organizations currently in the AI landscape.

Who Is Designing AI Platforms?

If you’re considering implementing AI in your business, there are four categories you’re likely to run into.

AMG (the Clouds). These are the major cloud service providers like AWS (Amazon Web Services), Microsoft Azure, and GCP (Google Cloud Platform) that are implementing AI. The advantage of this option is the size of information they have access to. The disadvantage is that these organizations seek to lock you into their platform, making it difficult to move data from one cloud to another.
Meta. Meta is an open-source AI platform that allows you to integrate with other platforms you might be using. The challenge here is that you need to have a team of experts who understand integration or who can leverage the existing code with any new code you need written.
Legacy SaaS. These are ERPs (enterprise planning tools) like Epicor and CRMs (customer relationship management tools) like Salesforce. Through AI, many of these platforms can now help you mine additional information from your data, helping you make more informed decisions. The disadvantage is that moving that information and those insights into a competing platform can prove difficult, leaving you locked in.
Startups. You likely hear of new AI players entering the market on a daily basis. While this breeds creativity and agility, the challenge is that AI requires a great amount of capital and talent, and many of these new companies fail before they even get started. This makes it challenging for organizations that implemented their software early and are left hanging.

What does this mean for your organization? It means that you need to carefully consider which tools are right for you and your business goals. We’ll talk more about that in a bit.

How to Build AI into Your Business

In 2024, 77 percent of companies are either implementing AI into their business or are considering it. For C-Suite executives and decision-makers, it’s not about finding the perfect tool—it’s about asking the right questions. Let’s discuss some of the important questions you need to answer before implementing AI.

1. Should Your Organization Restrict AI?

To answer this question, you’ll need to understand the following:

Legal implications. Does your industry have specific compliance requirements that will force you to restrict AI? If yes, then help your employees understand this as you restrict AI.
Employee compliance. How likely are restrictions to actually work? Does your workforce need additional training to understand the importance of compliance?
AI tools with guardrails. Are there AI options that you can leverage to meet your employees’ desires for creativity but that have some limitations or built-in restraints?
Leveraging creativity and efficiency. Can our employees implement AI to improve efficiency in their workload?

Unless you have to meet strict compliance regulations, keep an open mind when it comes to implementing AI. The popular saying goes, “I choose a lazy person to do a hard job. Because a lazy person will find an easy way to do it.” Use your employees to find those efficiencies. They have a ground-level view of productivity pain points you might not see. AI can often answer those inefficiencies.

2. What Should We Do with AI?

So you’re thinking about implementing AI but not sure how to use it. Consider the following to determine how you might leverage AI in your business:

Think outside the chatbot. As you review your tech stack, are there core problems not being addressed? Is there an AI answer for that issue?
Narrow scope, clear goals. For stronger buy-in from employees and key stakeholders, consider how you can prove the value of the AI you implement whether through reports, ROI, etc.
Iterable. Avoid spending capital on dead ends. Rather, promote AI projects that have promise.
Integrate with strategy. Select AI that is closely aligned with core business strategy and tied to revenue or AI really won’t help you.

The key is to be agile and consider the tools that align with your industry and your goals. AI should not be a one-off tool that does little to improve your bottom line or efficiency.

3. How Should We Integrate AI?

Now that you’ve identified your AI project, let’s talk about putting it into action and some things you need to watch out for:

Identify your risks. It’s imperative to keep a pulse on the regulatory environment. Will you be liable if something you share has a copyright issue or includes a bias? Some AI platforms will take responsibility while others may not—leaving you holding the bag.
Understand your data. Output is only as good as the inputs. Make sure your data is clean, organized, in the right place, and ready to be fed into the AI model you’ve chosen. If you’re not currently collecting the data you want to analyze, start now!
Build vs. buy. Knowing when to build your AI system and when to buy it will depend upon your resources, how much risk you want to take on, and who owns the data. Do your homework before landing on a solution.
Plan to fail. Failure can be a powerful learning experience. Define what failure may look like and how you can ensure you learn from those mistakes.

Now that you’ve prepared for implementation, let’s talk about what’s next to put AI to work for your business.

4. What’s Next?

By now you should feel more confident in your decision to implement AI. AI can be a great ally in executing your strategic plan. There are a few key things you’ll want to remember as you add AI to your technology stack:

Humans required. While AI is becoming increasingly powerful, you still need a human eye to ensure you are getting the quality outputs you desire. Whether it’s a chatbot response to a customer request or an AI-generated image for a company video, it’s up to your team to maintain the tone of voice, authenticity of the brand, and accuracy of the information shared.
Minimize anxiety. Gallup reports that 22 percent of employees are concerned that AI will replace their jobs. Make sure you are open about your AI strategies with your employees. Convey to them that you aren’t replacing humans with AI but that you’re improving their workload by implementing AI.
Stay abreast of trends. The landscape of AI is ever changing. Stay ahead of those trends! Those who learn and adapt to AI quickly will have a competitive edge with first-mover advantage.

AI can be a powerful tool for organizations that understand what it is, how to implement it, and how to overcome the challenges that come with it. If you’re wondering when a good time is to start implementing AI, the answer is now! Educate yourself on the current AI landscape, determine what AI tools may alleviate your company’s efficiency or creativity roadblocks, and then determine if AI is right for your business.

This article was written based on the session conducted by Nick Pelican at Ampleo’s 2023 CFO & Growth Summit.