Artificial intelligence in business is not going anywhere. But every other headline warns about the dangers of AI. It’s easy to get caught up in the hype and to associate those negative headlines with all types of AI.
But there is a critical distinction between various applications of AI that not many people know about: Generative AI vs Applied AI.
AI education is extremely important. AI tools can save business leaders time and money, and customers deserve to understand the benefits and risks of using them.
News outlets like Bloomberg and Business Insider have endlessly reported on the generalized risks of AI. These fear-based articles go in-depth about why Gen-AI is risky; and as we know, fear sells. These news outlets have no interest in explaining the difference between generative AI and applied AI.
Artificial intelligence in business can be applied with minimal risk, and we want to make sure you know the difference between the two types of AI applications.
What is Generative AI?
Generative AI tools use a huge dataset to create new content. They typically scrape the entire internet (including your emails, text messages, and voice messages), and then use that data to predict what comes next in a sequence. Popular Generative AI tools include Dall-e, Midjourney, copy.ai, and ChatGPT.
There are huge risks when using GenAI within a business. Most of the available tools are public AI and draw from mass public data, so it’s impossible to know exactly how your data is being exposed. Because of this, it’s difficult to maintain compliance while using GenAI.
There are some benefits to Generative AI. Because it's a public AI, it’s available to anyone. It does provide some productivity gains, although they tend to be small. Writing a faster email isn't worth the risks that come with using public AI.
What is Applied AI?
Applied AI tools are used to solve specific problems in specific environments, such as process automation for certain tasks. Although AI is getting a lot of buzz right now, applied AI is not new. IBM, Palantir, and even Wall Street banks have been using these kinds of tools for decades.
Applied AI does not come with the same risks as Gen AI. Applied AI is used for proprietary data, confined within an organization’s firewalls. Solutions like Terzo have protocols for handling sensitive information such as financial or risk data. And importantly: these tools are using your data to improve outcomes for your business only. Your data is not being used to improve businesses around the world.
Applied AI in the Future
Given all the risks and benefits of each, we believe that applied AI is the most likely to be in production environments in the near future. Applied AI can quickly and efficiently add value to your business with smaller-scale, specific use cases.
At Terzo, we have made an ideological choice to apply AI within confidential, proprietary data sets, using a customer’s data to benefit only their organization. We do not use tools that draw from public sources of information. Because of this, we can get immediate results for our customers, without exposing them to unnecessary risks.
We understand the reluctance to adopt AI tools, but putting off adopting applied AI only delays your progress toward modernizing your business, completing routine processes faster, and saving time and money alongside first-movers in your industry.
With Terzo, you can take a process such as manual contract review and easily automate it. Documents that used to take a team of 12 people 8 hours to review now can be done in seconds, so your team can focus on making informed decisions. With fast, actionable data, you improve team performance overall.
When evaluating what kinds of AI tools to bring into your business, look at your most important short-term problems. Big ideas might be fascinating to think about, but smaller applications give you the results you need now.
If you’re ready to see how Terzo AI can add immediate, measurable value to your business, reach out to the team at Terzo for a free consultation.
