The push to leverage what is shaping up to be the most impactful technological advance in recent memory has been tremendous. Following AI best practices ensures that this momentum translates into sustainable, responsible, and high-value outcomes for businesses and their teams.
The result has been predictable. Estimates vary, but at least one pegs the failure rate for AI implementations between 70-80%, and most other estimates are similarly disappointing. Keeping pace with industry peers is definitely sound business, but implementing this promising technology solely for the desire to slap a new “now, with AI” label on a product or process may not be the most productive approach.
The Myth of “Plug-and-Play” AI
While some companies are offering AI tools and platforms that simplify the integration of AI, they all require some level of customization and planning to meld seamlessly with existing infrastructures. The complexity inherent in any attempt to utilize an AI solution is important to fully grasp.
One CEO of a major supply company, Spencer Fung, put it aptly: “Companies acquiring AI without a new business model is like a company digitizing a horse and carriage—while the competition has created a digital automobile.”
AI should not merely be considered as another tool for an antiquated toolbox, but as an opportunity to reexamine and revitalize all the tools being used for business functions. A solid strategy including AI best practices for not only implementing AI but also preparing an infrastructure to receive it is critical.
Infrastructure First
These seven best practices that will follow and how they are ultimately applied will vary from business to business, but the network infrastructure at the foundation of any organization that might prosper with the addition of AI solutions has universal demands.
Business-class Internet or Fiber capabilities are critical. The speed, responsiveness, and scalability of your Internet service are indispensable for getting the most out of adopting AI. AI works fast and requires a reliable connection that can keep up.
Additionally, a secure cloud computing platform is also a must-have. The cloud has already seen widespread adoption for its value in facilitating rapid and safe communication between integrated systems, as well as augmenting the data storage capacity and processing speeds for supported applications. Introducing AI into an ecosystem can make these benefits a prerequisite.
The advent of AI has generated some very valid security concerns, and this is where private networks can be brought to bear. By siloing sensitive information and systems needed for the AI’s functionality into distinct, secure networks, companies can exercise stricter control over the inputs and outputs of an AI solution.
Seven AI Best Practices
Here are seven best practices to follow when creating your AI-ready, AI-first tech stack.
AI Best Practice #1 – Employ a Human at the Helm Strategy
“Human at the Helm” is a principle that emphasizes keeping people in control of AI systems rather than allowing automation to operate unchecked. Instead of treating AI as an autopilot, this approach positions humans as strategic decision-makers who steer outcomes, apply judgment, and uphold ethical standards.
It goes beyond “human-in-the-loop” by focusing on system-wide governance. Humans set boundaries, review high-impact decisions, and ensure transparency and accountability, while AI handles repetitive or data-heavy tasks. This balance leverages AI’s efficiency without sacrificing human values like empathy, context, and trust.
It may be the most critical AI tactic because unchecked automation can amplify risk, bias, misinformation, or even catastrophic errors…at scale.
AI lacks a moral compass and cannot assume responsibility; humans provide ethical oversight, contextual understanding, and adaptability in complex scenarios. By keeping a human at the helm, organizations safeguard against blind spots, maintain accountability, and build trust with customers and stakeholders. In short, this tactic ensures AI remains a tool for augmentation, not abdication.
AI Best Practice #2 – Centralize Clean Data
As many organizations are finding out, AI is only as good as the data it consumes. The more data AI has to work with, the better the results will be—but it has to be the right data. Before AI is ever switched on, time needs to be allocated for the curation of data. The data fed to AI should only be what it needs to do the job, and it is frequently a good idea to locate that data in a centralized store, mitigating the need for AI to pull from too many disparate sources. The latter not only aids in data format consistency but also in security.
AI Best Practice #3 – Build on Cloud-Native, API-First Platforms
Another way to make sure AI is receiving the exact right inputs it needs to perform is to utilize well-developed APIs built on cloud-native platforms. This means that the cloud and APIs used to integrate AI functions are integral parts of the infrastructure, not just technologies installed as add-ons down the road. These APIs are more highly developed to drive the correct traffic between systems, and they contain more configurable functionality than just simple connection points.
Cloud native means the infrastructure is built around leveraging the cloud, rather than trying to shoehorn the cloud into an existing solution. This type of platform can be eminently more scalable and flexible than many legacy systems.
AI Best Practice #4 – Adopt Modular, Interoperable Tools
While isolating certain aspects of AI functionality is desirable in terms of security, other aspects of an infrastructure will doubtless need to become more interoperable. Fostering collaboration should be one of the main goals of an AI endeavor, allowing systems to communicate more fluidly. These tools can also lend to a higher degree of scalability, which is important when adopting a technology that is well-suited to growth and flexibility.
AI Best Practice #5 – Infuse AI into Workflows, Not Just Apps
The interoperability key to a successful AI deployment also lends itself to a frequently overlooked benefit of AI: managing workflows. Too often, AI is deployed as just another add-on application that has to be manually called into service. This ignores the virtually limitless potential AI has to streamline and accelerate business workflows. AI’s ability to make nearly instantaneous decisions using vast data sets makes it a perfect candidate to create more efficient and accurate business processes.
AI Best Practice #6: Prioritize Security, Privacy, and Governance
The collaborative nature of a solid plan for AI integration also benefits significant security considerations. A recent study found that almost 70% of IT professionals surveyed viewed the rapid advancement of AI as their biggest security risk.
The promise of AI comes with peril, and it’s important that this risk is identified and thoroughly mitigated before using AI in day-to-day operations. Security is not a new concern for IT shops, but AI has changed the landscape and could represent an acceleration of unmanaged vulnerabilities if not implemented thoughtfully.
AI Best Practice #7: Prepare for Agents and Automation
Is your infrastructure ready for AI? Since the best approach to implementing this exciting technology involves collaborative integration, it is imperative that your infrastructure is orchestration-ready. This may involve some difficult decisions around the current state of your tech stack, but it is important to make sure that the existing infrastructure is ready to take full advantage of your AI goals. Using agentic AI to augment workflows and automate specific tasks requires careful planning and an ecosystem built to accept AI as a key participant in operations.
Is Your Business Ready
There is a lot to consider when evaluating your company’s infrastructure for AI readiness, especially if you are looking to maximize the return on your investment. AI is more than just a new coat of paint; it has the potential to redefine and revitalize the way you do business. An experienced technology partner can be an invaluable partner in this bold venture, and this is where Cox Business experts come in.
Learn more: https://www.coxbusiness.com
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