Measure twice and cut once. It’s an old woodworking truism that applies to the building of anything. For small- and medium-sized businesses contemplating their artificial intelligence strategy, the advice is especially applicable.
According to a September 2024 report from the U.S. Chamber of Commerce, nearly every small business in the U.S. (98%) currently utilizes at least one AI-enabled tool or application, and 91% believe it will help them grow. The Chamber of Commerce also cited that SMB owners who fully embrace AI technology are currently outperforming their peers and exhibit greater optimism about the future.
If SMBs’ early optimism and success is to continue, owners must understand the drivers and trends moving the AI market forward. Among these are an increasingly diverse and complex landscape, AI’s impact on the IT network, and the critical need for a carefully considered AI strategy.
Navigating the landscape
The AI market is crowded and complex. Applications and tools come in all shapes and sizes. Free downloads or online tools (think ChatGPT), embedded within existing software packages, fee-based plugins from software vendors, customized applications built from scratch and more. They can be hosted on your network or in the cloud; some are resource-intensive, while others can run on any off-the-shelf laptop, computer or even cell phone.
With so many options, any decisions regarding a potential AI investment must be thoroughly considered from every angle. What resources are needed and at what cost, how will it impact employees and customers, do you have the right data to generate the necessary results, what’s your deployment schedule and strategy? The ultimate question that must be answered is: does the estimated ROI exceed the total cost of ownership?
Navigating this process is complex and time-consuming. Not surprisingly, an entire industry has sprung up to help SMB owners make the right decisions. The global market for AI consultants is growing at 39% annually and expected to reach $630 billion by 2028.
Right sizing your network
As AI applications grow more powerful, the network resources required to support them also increase. The degree to which the network needs to be upgraded, if at all, depends on the volume of data involved and where the engine is located.
There are two main data components for any AI application. One is the input data that the application will use to make predictions, automate tasks, etc.; it can include things like sales data, product testing information and a customer’s purchasing history. The other is the AI engine itself.
The location of the data and the AI engine can significantly impact the network resources you need. If both sets reside on your network, the impact on network capacity, speed and latency can be minimal. If the resource data is on site and the AI engine is in the cloud, the data must be shuttled back and forth between the business’s network and the cloud. Without enough bandwidth, the AI application creates a bottleneck that affects all network traffic. For applications designed to deliver near real-time results, such as manufacturing automation and asset tracking, the network’s latency performance becomes a third impacting factor.
Prior to selecting and implementing any AI application, it is important to understand the current operating state and capacity of the business’s network. Enterprise network performance monitoring tools are available from most network service providers. Among other things, these tools typically measure how much network capacity is being used and how much is left over for data-intensive AI applications.
Choosing wisely
SMB owners have much to gain by making sound AI investments. Alternatively, the results can be catastrophic if the decision isn’t made carefully. Good decisions begin by being strategic in which AI applications you implement.
Start small with low-hanging fruit
Before you shell out the money and time to create a bootstrap AI program from scratch, see if the same capabilities already exist. A good place to start is with your existing software companies. For example, if you’re looking to add predictive analytics to your marketing program, contact your CRM provider; they may have a simple plugin already built. If not, they may know who does. A secondary option would be to go online to see if something similar is available. A major difference between these two options is that working with your existing software vendor should not compromise your data’s security (as you’re already working with the vendor). The second option could introduce a security risk, assuming the AI application cannot be hosted on your network.
Pick projects with measurable outcomes
If you can’t quantifiably measure the results of your investment, how do you know if it was successful? Measuring results begins by understanding what outcomes you can expect and setting concrete goals. You may be considering a productivity tool, for example. How will you measure the results? By the number of units, cost savings, employee retention? At the end of the pilot program, you need to know whether the return was worth the investment. If so, you know you can begin to scale the program up.
Keep it in-house, if possible
As mentioned earlier, there are resource implications when trying to shuttle large amounts of data between your facility and the cloud. Keeping the AI engine onsite is one way to mitigate the cost of upgrading your network. Another reason to house your AI capabilities locally is security. While cloud-based AI platforms take care to protect customers’ data, breaches have and will continue to occur.
What is my security risk?
Finally,know that anytime you deploy or use an AI application or tool, you increase your organization’s risk of attack and, by extension, the privacy of your customers.Like the applications being targeted, the attacks are becoming more sophisticated and costly if successful.In a hyperconnected society, this is the new reality. It shouldn’t prevent SMB owners from pursuing AI opportunities, but it must be seriously considered. Before adopting a new AI application or tool, consult with your network provider to understand and mitigate the security risks.
Jump in (but look before you leap)!
AI, in all its forms, has the potential to help level the playing field for today’s small- and medium-sized businesses. From automating routine, time-consuming tasks to providing deep insight into products, processes and markets, technologies like generative AI, AI agents and conversational AI can help owners work smarter, plan better and provide a better customer experience. As with any new and disruptive technology, it will take time for the market to stabilize. In the meantime, the AI landscape will continue to be a bit frenetic but filled with opportunities for those willing to take a measured approach. Literally. Measure twice and cut once to build a better future for your company.
The views expressed in this article belong solely to the author and do not represent The Fast Mode. While information provided in this post is obtained from sources believed by The Fast Mode to be reliable, The Fast Mode is not liable for any losses or damages arising from any information limitations, changes, inaccuracies, misrepresentations, omissions or errors contained therein. The heading is for ease of reference and shall not be deemed to influence the information presented.
