artificial intelligence

More than half of businesses now use artificial intelligence (AI) for cybersecurity, 46% are leveraging AI Integration to create internal communications and a whopping 97% believe that new tools such as ChatGPT will help their business.

The numbers make it clear: AI is gaining ground to advance business goals.

For many organizations, however, there’s a disconnect between AI potential and AI in practice. Put simply, if companies can’t effectively implement AI tools, investments won’t pay expected dividends and benefits won’t materialize.

In this piece, we’ll explore the evolving role of business AI, pinpoint possible paths for new solution success, and offer six steps for effective AI integration.

AI IntegrationThe Evolving Role of AI

Artificial intelligence tools are capable of completing specific, data-driven tasks without the need for human input. They accomplish this using what are known as machine learning (ML) algorithms. Using a combination of preprogrammed criteria and access to large datasets, it’s possible for programs to “learn” over time and produce consistent results.

Consider an AI tool that examines images to determine if the image contains a dog, and if so, its likely breed. To make this possible, the tool uses multiple ML algorithms. For example, one algorithm might be trained to differentiate between dogs and other animals, such as cats or horses, based on specific physical characteristics. Another algorithm could use large data sets to learn what physical characteristics are common to specific dog breeds.

The result is a software solution that’s incredibly accurate but doesn’t “learn” like a human — instead, it uses human-created rulesets to mimic the learning process.

New solutions such as ChatGPT have leveled up this process. These generative tools can understand natural-language queries and questions and producing human-like responses that demonstrate both understanding and insight. At their most basic, however, these tools are advanced calculators for words — with the right inputs, they deliver correct answers.

Potential Paths to AI Success

As AI tools evolve, there are several possible paths to success.

First is using AI to uncover new data relationships. Given the exponential growth of data, AI is quickly becoming the most effective option for this process. Many companies now have data across multiple on-site and cloud-based environments and that is stored in differing formats based on its purpose, potential security risk and use case. Artificial intelligence tools can collect and combine data from disparate data sources to uncover previously unknown connections.

Artificial intelligence can also be used to help predict human behaviors. For example, by using a combination of historical customer transaction data and recent purchase habits, AI tools can determine if customers are likely to spend more, spend less or spend the same in the future.

Finally, generative AI tools such as ChatGPT open the door to more free-form insights. Consider the recent announcement that ChatGPT will soon be able to ingest and interpret data from across the Internet at large. With this much data available, along with an advanced natural language processing (NLP) engine, businesses will be able to ask even more in-depth questions and receive clear, usable answers.

Six Steps for Effective AI Integration

AI offers power and potential, but only if these tools are effectively integrated. While simply tacking AI onto existing processes may offer some benefits, it may also cause operational roadblocks if current frameworks aren’t designed for AI or if staff prefer more familiar tools.

Here are six steps to help streamline the transition.

  1. Pinpoint an AI project

AI tools can potentially perform any number of tasks. As a result, it’s easy for companies to adopt a broad AI approach. The problem? Maximizing the value of each new addition. With multiple projects underway simultaneously, companies can get bogged down in the details. Selecting a single project lets teams focus their efforts and ensure current tools can effectively integrate with new solutions.

2. Consider your options

As the AI market expands, more options are available. Organizations can now choose from stand-alone products, platform-based solutions and free-to-use solutions. Which one(s) makes the most sense depends on current business goals and targeted outcomes.

3. Ask for feedback

Before implementing any AI solution, ask for feedback from anyone who will regularly interact with AI tool or leverage its results. Not only does this offer a chance for staff to familiarize themselves with new solutions, but also it can identify potential pain points.

4. Start small

AI isn’t going anywhere, so there’s no need to rush your deployment. Instead, start with a small-scale test and see how tools perform. If results are promising, scale up. If not, start over. By starting small, businesses can reduce the risk of wasted resources.

5. Gather data

Artificial intelligence tools are only as good as their last results. To ensure consistent performance, companies should continually collect data and compare outcomes with target metrics.

6. Apply AI at scale

The last step in AI integration is applying tools at scale. This could mean expanding beyond local data sets or asking more in-depth questions of AI tools. Worth noting? This isn’t fire-and-forget — businesses are best served by regularly reevaluating solutions to ensure they’re performing as intended.

Artificial Intelligence, Real Impact

AI adoption is rapidly increasing, and thanks to the evolution of NLP and generative tools, the impact of AI and ML has moved beyond the theoretical into the realm of the possible and the practical. From better predictions to increased understanding to actionable insight, AI is paving the way for a new business framework.

AI in isolation isn’t enough. For companies to make best use of smarter, faster, and more powerful tools, effective integration is essential. Comprehensive IT infrastructure management services can help you reach these goals.

Author bio: Jody Jankovsky is the founder and CEO of Black Line IT, serving over 500 clients in 30 years and earning spots on Inc. 5,000’s Fastest Growing Companies list twice. Recognized in the Chicago Tribune, renowned brands rely on his tech expertise. Jankovsky is also a key speaker on technology, cybersecurity and business software.

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