One area where AI tools can help even the smallest business is in sales and marketing. Every business is marketing and selling in the online digital world. Marketing on social media is a given for every business, and can be a game-changer for a small startup. However, a lot of the tasks of marketing on social media and through your website can involve tedious, time consuming tasks. Marketing tools that use AI can help with drip email campaigns, website visitor tracking, and understanding where each customer exists in the sales funnel at any given moment. Other digital tools that increase customer engagement and drive sales are available and are an excellent introduction to AI as a marketing tool. Using these tools, you can focus your limited sales resources on other, more critical tasks such as closing a sale with a customer that is now ready to buy and not simply exploring vague options. These AI tools are readily available and your MSP can guide you in the adoption and use of them

AI and that data you collect. An MSP or MSSP can also be a resource for data protection. As you begin using such tools, you amass enormous amounts of data about prospects as well as customers. How you hold, use, transmit and store this data is subject to some data regulations, either by your state, a federal agency, or even the European Union. Regulation is growing because of the increasing concern about an individual’s online privacy. Because so much personal data is being collected about each of us, there is increasing concern about misuse of that data, protecting it from bad actors, and other privacy rights issues. While you may not be physically located in a state that has data privacy regulations, if you conduct business in a state or country that regulates data privacy, you are likely subject to their rules. An MSP or MSSP is an important resource to determine where you are subject to those laws. More importantly, if you are subject to those laws, (e.g. HIPAA, The FTC Safeguard Rules, the CA Privacy act or the General Data Protection Regulation of the EU), you may also be required to prove that you have developed protocols for the protection of data as defined under those regulations. It isn’t enough to say “everything is safe.” You may have to provide evidence you have created the specific data protection protocols specified under the regulation.

In short, AI can be a helpful tool to grow your business, but it comes with responsibilities and concerns that may not have concerned you before. An MSP is an important resource as you wade into the world of marketing, sales, and other operational areas.

Are there risks to AI? Absolutely. There are end-of-the-world predictions about the use of IA. For a business, many of the risks are a bit less extreme, but they are also very real. For example, in the area of content creation. There are a variety of risks that you open yourself up to. One of the key ones is the trustworthiness of the content created. You rely on generative AI to create an accurate explanation or description of a topic, event, thing, or idea, However, can you, in fact, completely rely on that? The answer is probably a qualified no. The level of “qualified” depends on a variety of factors. Your AI generated content is only as good as its sources, and that can create real questions for readers. Also, an organization using AI to create any type of video, text, image, or audio content needs to be concerned that it may include proprietary information that you need permission to use. Could material created by generative AI suddenly veer off into copyright infringement?

AI is also being used in areas such as recruitment. However, there has been research suggesting that bias can sneak into AI decisions as a result of the source data the tools are using. Bias is a concern not limited to the one example of recruitment. It can have consequences in areas where AI is making marketing decisions, and can taint medical and legal recommendations AI might provide. As a result AI cannot go “unmonitored.” Review by humans and other tools is a best practice that is needed to improve accuracy and trustworthiness. This, in turn, may cut into the efficiencies that are perceived to be created by AI. Also, a lot of AI–Chat GPT to just take one example–isn’t going to necessarily incorporate consideration of regulation and compliance requirements. Many countries, individual States in the US, and US federal agencies are implementing data security regulations that are designed to protect the Personal Information of individuals. In many cases violations include civil penalties. In the case of the European Union’s General Data Protection Regulation, fines are significant.

If you are considering stepping into AI, your MSP can provide guidance. Our recent list bears repeating: Eight ways an MSP can help you approach an AI solution.

Step one: Assess potential uses of AI. Your MSP should have a solid understanding of your entire business and how AI might contribute. They can help you start with small steps and move from there.

Step two: Understand your KPIs and organizational goals, from the top down. Before jumping off and adopting AI just because it is there, evaluate your KPI’s. Where do you perceive you need a boost?

Step three: Propose a possible range of AI solutions. An MSP will be knowledgeable about the variety of applications out there and lead you to select those most appropriate for your goals. Remember, they should be directed toward assisting KPI improvement.

Step four: Estimate the solution’s ROI. Remember, measurement is important. And you can not do everything. So identify each potential AI solution’s ROI. As mentioned above, AI isn’t just a trendy tool to adopt just “because.”

Step five: Ensure compliance: For example HIPAA, PCI. HITRUST. ISO27001, SOC1, SOC2. AI is a powerful and potentially intrusive tool. Compliance is critical.

Step six: Implement the solution. An MSP can implement the solution for you. Most business owners do not have the resources available for what can be a time-intensive project.

Step seven : Manage tool-related risks. As noted, there are best practices. Monitor to ensure your outcomes with AI are accurate, trustworthy, defensible, transparent and meet regulations.

Suddenly, everyone is talking about artificial intelligence (AI). It is constantly in the news now. It suddenly is looming like some intimidating Terminator. However, AI is not a toggle switch that was suddenly turned on one day this year. AI is everywhere and has been around for far longer than most of us are aware. We just didn’t realize it.

Ever think about how Instagram shows you reels based on your past views? Youtube does the same. Amazon makes recommendations based on your browsing and purchase history. By the newest standard, that is old hat AI, but it is AI. Lately, significant advances have been made that increased the power of these learning algorithms exponentially. The new tools Chat GPT, BARD, Well-said are examples very widely covered in the media.

Why are businesses so interested?

There are a wide variety of uses for AI in the business space, from project management to customer service.
A bit of background, it might be helpful to take a quick survey of places where AI is being deployed.

Before looking at examples, let’s discuss why use AI in any area at all?

Given technology, any organization has the capacity to collect–from the perspective of a human–an incomprehensibly large amount of data on almost any subject. This data can be used to do many things, but there is so much of it, we have a limited capacity to see patterns and synthesize. AI has the capacity to do that.

Three examples:

Demand forecasting in retail: Who doesn’t want the magic bullet to decide how much to stock for each season? However, just observing how much sold this month last year isn’t a sufficient predictor. What about the weather? Bad economic news. Construction on a nearby road that is now finished this year. The endless factors that may influence buying decisions can be used to forecast demand more accurately.

Disease screening in healthcare: AI has the capacity to potentially use data to identify or eliminate certain diagnoses that an individual medical professional whose experience is necessarily finite, might be able to do. Like much else, there are ethical issues that can make AI a complex tool, but there is much potential.

Customer retention: Like other areas, you probably can collect more information about your customers than you can make sense of. So, why did they leave? You may have the answer, but it may actually be a calculus of many factors. AI can help identify all of the issues that may have led a customer to leave. Without AI, you may incorrectly attribute it to one single factor.

Why are marketers so interested?

AI has potential applications in the marketing end of any business, large or small. Marketers, in particular, may find AI useful in these three general categories-

Collecting Data about prospective customers – Even small businesses can collect a significant amount of data. AI can allow you to analyze that data. No matter how much data you collect, it is useless unless you can synthesize it, see patterns, etc. The human capacity to make sense of the massive amount of data we collect is limited.

Using data to market more effectively – Even the most novice marketer knows that the more you know about each prospect the easier it will be to target them. The more you know their needs, the more you can explain how your product or service meets those needs. AI allows you to do more with the data you collect- to make sense of it so you can use it.

Generating the right message – AI may be also able, to a certain degree, assist you in creating the messaging to reach your target. However, it is important to recognize that AI is not a silver bullet.

In short, AI may offer you some new tools to more effectively market without expanding your present marketing resources.