Novelty or Necessity–Should You Implement AI Into Your Business ASAP?

Remember the beverage "clear craze" of the 80s and 90s? From Crystal Pepsi to Zima, these drinks were marketed on new science and novelty, but they ultimately failed because they did not offer genuine improvements in flavor or health.

Today, standing neck-deep in the AI craze, many businesses are tempted to integrate this new technology into their operations without a clear (see what we did there?) strategic purpose. With everyone from Instagram to Swarovski bolting AI onto their products as quickly as possible, it can feel like any delay will equate to irrelevance.

While technologically sophisticated, many of the AI offerings we see popping up serve more as a novelty than a functional enhancement. And if the cost of development is high, this leads to a poor ROI. So how can you put your money to its best use and take advantage of the incredible potential of AI? Let’s look at some do’s and don’ts of implementing AI into your business.

Do Lead With Strategy: Know Why You’re Integrating AI

Integrating AI without a solid strategic foundation can lead to problems such as disrupted user experience, unnecessary features that bloat software, and wasted resources. To avoid this, businesses must clearly define the “Why” of their AI implementation.

For example, a company might introduce AI chatbots for customer service because, well, hasn’t everybody? And yet, how many of us have had infuriatingly pointless conversations with chatbots when what we needed was human customer service? Chatbots are perfect for simple inquiries and FAQs. But if the bulk of your customer service is dealing with complex inquiries, chatbots won’t be able to effectively handle them.

Analyzing the “Why” and the “Jobs to Be Done” that you hope AI will help with and comparing that to your larger business goals will keep you from investing in tools you don’t need.

MIT fellow Sukwoong Choi mentions in a new paper that “the positive relationship between AI adoption intensity and revenue growth is stronger among firms that pursue a more exclusive R&D strategy specific to the venture.” Basically, the more thought you put into why AI can help you, the more profitable the implementation is likely to be.

So ask yourself:

• Have I clearly laid out my business goals and what I hope to achieve with AI?
• Have I defined milestones for its implementation?
• Do those milestones align with my business’s core objectives?

AI projects can be costly and complex. Without a clear strategy, resources might be wasted on initiatives that offer little return on investment.

Do Give It Time: Successful AI Integration Requires Patience

Businesses often underestimate how long it takes to apply AI models to their custom tools—particularly because “data modernization” is required before they can even begin utilizing AI features. This entire process can take anywhere from 3 to 36 months.

You will need to assess, clean, and convert your data into a format that AI can work with. It will need to be updated on an ongoing basis. Your current systems may require upgrades in hardware or cloud capabilities in order to support AI workloads. If applicable, privacy and usage rights will need to be considered. If you're using customer data, you'll need to ensure you're complying with all relevant laws and have the right permissions in place to use that data for AI purposes.

All these steps take time—often more than you might expect. It's important to plan accordingly and give your team the time they need to do it right. Rushing can lead to mistakes that could cost more time and money to fix later on.

Don’t Drown in It: Assess Your Data First

When you perform a Google search, the staggering number of total results teaches a valuable lesson—we live in a world overflowing with data, much of it algorithmically matched but not necessarily relevant to our needs.

In many organizations, data is spread across a variety of silos. It’s found in structured systems like sales databases, CRM, ERP, HRM, marketing, and finance platforms, as well as unstructured formats such as emails, text messages, voice messages, and videos. Depending on the scope and complexity of your project, you might also want to bring in new, external data sources, like public domain data.

But be careful not to try to apply AI to all this data without a plan. Instead, assess the value of the information you currently hold or could potentially acquire. For example, if you are a retail company and you try to use AI on all your data—including outdated inventory from years ago or irrelevant customer emails—you might end up with confusing or misleading insights. This could lead to poor business decisions based on faulty information.

Instead, you need to focus on the information that directly relates to your goals. If you’re aiming to improve current sales, you should concentrate on recent sales data and current market trends. You should clean out or archive old or irrelevant data that could clutter your analysis. This streamlining process not only minimizes risks but also reduces the burden on your systems, ensuring that your resources are focused on processing and protecting data that genuinely adds value to your operations.

Don’t Go It Alone: AI Implementation is a Team Sport

Implementing AI with partners can significantly enhance the effectiveness of your project. Partners can bring specialized expertise, advanced technology, and additional resources that might be too costly or time-consuming to develop in-house. For instance, academic institutions can provide cutting-edge research insights, while technology vendors offer platforms and tools that accelerate deployment. This approach not only speeds up the implementation process but also enhances the scalability and adaptability of AI within your operations.

According to Harvard Business Review, the companies most successful at AI implementation are those that work with a wide range of partners and consultants. This is even true for very large companies with deep resources. The article states that these companies, “despite their higher capabilities, actually relied more on external partners to further accelerate their learning and time to impact.”

Do It For the Right Reasons: Make Your Business Better

Strategy is key. It all starts with a clear idea of the specific challenges AI can tackle and how it fits into your broader business strategy.

• Will it boost efficiency?
• Can it spark innovation?
• Will it give you a competitive edge?
• Can it automate mundane tasks or improve customer interactions?
• From an ROI perspective, are the potential benefits worth the cost?

If AI is to become a fundamental aspect of how your team engages with data, stakeholders, and each other, establishing trust is crucial. Beyond ensuring your systems are compliant and secure, your team must be ready to fully embrace this technology.

Good AI implementation needs to provide the right solutions for the right situations. It needs to have the correct data, policies, and oversight mechanisms. You don’t want to end up paying for an expensive “solution” that no one ends up using because the results aren’t relevant and/or reliable. When AI solves real problems, your team will be excited to adopt it.

If It’s the Right Bandwagon For You, Jump On It!

Capitalizing on trends is not always a bad thing. Clearly Canadian was a strong survivor of the “clear craze” because, as a product, it was authentically aligned with the ideals that were being associated with transparent beverages at the time: healthier ingredients and better flavor.

In the same way, the path to successfully integrating AI into your organization is about making it authentically match your business goals and needs. By approaching AI with a well-defined strategy, patience, and a focus on relevant, actionable data, you can enhance your operations without falling into the trap of novelty.

If you decide to implement AI, get competent help. Partnering with experts will smooth your transition and leave you with a product that will continue to support your business long after the “AI craze” fades.