Separating AI Hype From Reality

Although artificial intelligence is one of the most talked-about technologies today, understanding how to practically integrate AI into your business can still be puzzling.

This is especially true for small businesses that may not have an in-house team of techies to help demystify trends and emerging technology.

However, with many software products embedding AI into their capabilities, the barriers to begin exploring AI are low. With some thoughtful goal setting and planning, any business can begin using AI in a way that delivers real value.

Before diving into any new technology, especially one as dynamic as AI, it is important to start with a clear objective. The real question is: What business problem are you trying to solve? Think about tasks and processes that require a lot of time to complete. That can help clue you into areas that need to be optimized.

Begin by identifying a specific need or use case. Are you looking to:

• Improve the customer experience?
• Reduce tedious, manual work?
• Enable data-driven decision making?

Without a defined business outcome and key performance indicators (KPIs) to measure success, your efforts can become misguided and an inefficient use of time.

AI is only as good as the data it's fed. It learns and operates by analyzing large datasets. Before diving into a large AI initiative, it is important to pause and consider if your data is trustworthy, accurate, accessible and able to be governed.

If your data is disorganized, inaccurate or incomplete, the results from your AI model will be flawed and unreliable. Before you can effectively leverage AI, you need to get your data in order. This involves:

• Cleaning up data: Ensuring accuracy and resolving inconsistencies.
• Consolidating data: Bringing information together from scattered, siloed sources into a more unified system.
• Establishing governance: Implementing security and privacy protocols to protect sensitive information.

Taking the time to prepare your data is never a wasted effort. It’s a foundational step that not only enables effective AI but also improves your overall business intelligence and can make it easier to adopt other technologies.

The excitement surrounding AI has led to several common misconceptions. Understanding these can help you set realistic expectations and improve adoption of new AI tools in your business.

• Misconception #1: AI will replace employees. The most effective use of AI is not to replace people, but to provide a tool that makes their job easier. From document processing to sales enablement, AI can help simplify and optimize various tasks across all types of roles. By reducing the monotonous, tedious parts of a job, AI can help your employees perform better and focus on higher-value activities.
• Misconception #2: You need a fully custom model. Many business owners believe they need an expensive, custom-built AI solution. The reality is that most small businesses can achieve significant results with existing Software as a Service (SaaS) products or platform-based solutions that offer a middle ground between off-the-shelf and fully customized. This is why it is important to set your business outcomes and KPIs early on. By focusing on what your business really needs, you can avoid over investing in a solution that does more than you need it to.
• Misconception #3: AI is a "set it and forget it" solution. AI models are not like software that you update once every few months. They require ongoing monitoring, governance and refinement. Models can "hallucinate" or provide incorrect information if not continuously trained and updated with new data and policies. At the end of the day, AI requires human oversight. It is important to elect at least one person on your team to review AI outputs for accuracy, ethics and brand alignment.

As many of us have experienced, using built-in AI tools or generative AI solutions is quite intuitive and user-friendly. However, implementing an AI solution that goes beyond that can be difficult. Being aware of the challenges around AI can help improve your implementation process.

• Data quality and accessibility: As mentioned above, poor data is the biggest obstacle to successful AI.
• Security and privacy: You must be cautious with sensitive data. Ensure any AI tool you use has clear security controls and that your data is adequately protected. Ensure only those who need access to sensitive data have it.
• Lack of internal skills: Small businesses often lack in-house staff with specialized AI knowledge. Partnering with an experienced technology provider can bridge this skills gap.
• Measuring ROI: It can be difficult to quantify the return on investment, especially when benefits are tied to productivity or employee happiness. Understand that you may need to focus on qualitative results to prove success.
• User adoption: If your team fears AI will take their jobs or doesn't understand its benefits, they won't use it. Clear communication and proper training are essential for getting buy-in.

Even if you don’t have a dedicated internal IT team, you can still implement AI. Many solutions are cloud-based and embedded in existing software, making them accessible without a large upfront investment.

The best first step is to start small. Identify a clear business problem, assess your data readiness, and explore accessible tools that can provide a quick win. Don't get caught up in the hype of doing everything at once.

Consider working with a trusted partner, such as CDW, that has deep technical knowledge along with an understanding of small business challenges.