Keys to Successful AI Projects and Maximizing AI’s Potential

Successful AI projects can radically boost efficiency, simplify operations, and improve customer experiences. AI has the power to transform your business, helping automate routine tasks, make smarter, data-driven decisions, and deliver more personalized services – but only if it’s done right.

Recent reports note a surprising 70-80% of AI projects fail. Why? Because leaders are inclined to use the same approach that worked for traditional software development projects. Additionally, these leaders lack planning and the right approach. Additionally, research from the Project Management Institute states that 88% of leaders have reported gaps in their project management practices when it comes to AI projects.

As a way to avoid AI project failures and boost critical ROI, let’s walk through how to plan, prepare and execute AI projects so your business can get the most out of this powerful technology.

Critical outlines for ensuring successful AI projects

Leaders can greatly reduce their risk of failure by carefully navigating the critical steps mentioned below.

Set realistic expectations from the project

It’s the CTOs’ or business leaders’ responsibility to explain the exact project details to stakeholders/consumers and what they should expect from it before they release it in the market.

Let’s say the management of a small local bank decides to implement an AI-powered chatbot in the bank’s app. The leader’s job, in this case, would be to highlight that while the chatbot can efficiently handle routine banking queries and transactions, it won’t be able to handle complex financial issues or provide personalized financial advice like a human banker.

Evaluate/consider before moving into AI technology

AI is not a 100% or a perfect fit for every business. Hence before moving into this revolutionary and powerful technology, CTOs should consider whether the AI models are resource-efficient alternatives that can solve the problem at hand. For example, some small businesses don’t need to implement AI-powered chatbots when a much cheaper automated email response system could be fine and effective.  

Cultivate AI literacy

Cultivating AI literacy within your organization will significantly improve AI adoption rates and employee trust in AI-based initiatives.  While it’s not necessary for every employee to be an expert in all aspects of the technology, a foundational knowledge of how AI tools and systems operate is critical for maximizing project success.

Few ways to achieve AI literacy are listed below:

• An internal AI summit (in-person or virtual) can be organized, that includes a series of informational speakers, vendor demos, and hands-on workshops.
• Upskilling programs across business units can be launched, to help employees develop new skills
• A reward or recognition can be announced for completing upskilling/reskilling programs, to encourage employees take the AI route.

Thoroughly monitor how AI solution is scaled

When planning to scale your AI solution, leaders need to be really careful about making changes to the parts of the product. Even small changes, such as using new algorithms or datasets, can sometimes make the product work differently than before. So leaders need to check that everything has been well tested before the product goes live.

Assemble cross-functional teams

Cross-functional collaboration is particularly important for AI project success. CTOs should ensure there is smooth communication and collaboration with project managers, technical  analysts, stakeholders, etc, to ensure all components required for the AI initiative are included and running successfully.

Define success and establish metrics to measure it

To measure the success of AI projects, organizations should establish Key Performance Metrics (KPIs).Well-developed and managed KPIs can help organizations ensure that their AI projects are not only effective but also adhere to ethical standard and legal frameworks, bringing measurable value to the business and to its users.

Include a human in the loop

Although this new technology has the word “intelligence” in its name, it still needs human oversight throughout its lifecycle, from its development and training to its operational performance and fine-tuning. A human with the right expertise and skills will make your project run better and increase its likelihood of success.

Focus on the prime business outcome, not the technology

CTOs need to keep a clear focus on the business outcome that needs to be executed through their successful AI projects instead of the technology that would be used to solve it. Just chasing the latest and greatest advances in AI for their own sake is one of the most frequent pathways to failure. Remember, no matter how impressive a new technology may appear, ultimately any technology—even AI— should serve the business purpose, not the other way around.

Know the limitations of each AI program

Finally, despite all the hype around AI as a technology, AI still has technical limitations that cannot always be overcome. CTOs cannot treat AI as a magic wand that can solve any problem or automate any process. Instead, leaders need to collaborate with technical experts to understand which kinds of projects are a good fit for AI’s capabilities so that they can deliver meaningful value to the organization. Simply assuming that AI can solve any problem risks setting the team up for failure.

Real-world example of AI project failure

McDonald ends AI experiment after drive-thru ordering blunders

In 2021, the fast-food giant partnered with IBM to test-run the AI ordering technology at over 100 McDonald’s locations. McDonald began testing AI drive-thru ordering to determine if an automated voice ordering solution could simplify operations for crew and create a faster, improved experience.

But later this year, in June 2024, McDonald ended its AI experiment with IBM over a slew of social media videos showing confused and frustrated customers trying to get the AI to understand their orders. One TikTok video in particular featured two people repeatedly pleading with the AI to stop as it kept adding more Chicken McNuggets to their order, eventually reaching 260. After many such mishaps and incidents, the fast-food giant decided to take a pause on its AI approach.

Preparing AI-ready CTOs and leaders for successful AI projects

AI is already making impacts across a wide variety of industries. Retailers, such as Walmart, are deploying AI for predictive analytics so that they know when to restock inventory and how to optimize their end-to-end supply chains. Pharmaceutical companies are using it to accelerate the pace and success rate of drug development. Meanwhile, in the defense realm, AI is guiding fighter jets, detecting enemy submarines, and improving commanders’ awareness of the battlefield. These examples demonstrate the relevance of AI to organizations in a variety of industries and for a variety of use cases.

As a result, CTOs and other business leaders often find themselves under enormous pressure to do something—anything—with AI to demonstrate to their superiors that they are keeping up with the rapid advancement of technology. But very few leaders have little understanding of how to translate this desire into action.

Hence, it is recommended that CTOs and engineers take the needed space and time to explore, understand, and curate the AI project, rather than rapidly shifting the team’s priorities and chasing something that is unknown. Leaders and tech professionals need to be worthy of such a long-term commitment —especially because an unplanned or unorganized AI project with an overly accelerated timeline is likely to fail without ever achieving its intended goal.

In brief

Successful AI projects have the potential to transform industries and foster innovation. However, navigating the path to successful AI deployments needs proper planning and approach from CTOs and other business leaders.