For many businesses taking the leap into AI can feel daunting.
Misconceptions about AI’s capabilities, unclear business goals, and change resistance among employees can see a project fail and instead result in confusion, misguided investments, and poor ROI. Despite these challenges, standing still is not an option – AI is a moving conveyor belt and if you stop you’ll be knocked off, argues Sandy Kahrod, Modern Work Product Manager at Six Degrees.
The key to avoiding these pitfalls lies in adopting a focused, step-by-step approach starting with clearly defined business outcome goals to ensure each AI initiative aligns with a measurable objective. And it’s not about jumping in headfirst. Targeted proof of concepts allow businesses to test AI applications in specific areas, avoiding the risks of premature large-scale rollouts.
Additionally, fostering a culture where change is embraced is essential for an AI project’s success and can be achieved by addressing team resistance through transparent communication and structured, ongoing training.
Let’s explore how businesses can balance caution with ambition and harness AI’s potential to secure a competitive edge without incurring the costly mistakes caused by overreach and inertia.
Cutting through the hype
Currently, the market is overwhelmed with a lot of hype from a lot of sources. The recent launch of DeepSeek is a great example of how AI can dominate the front pages, not just the tech pages. However, that also means there is a lot of bluster to navigate, meaning a balanced and critical evaluation of the benefits and limitations is key. Decision makers should focus on pragmatic steps that align with their specific business needs and avoid getting swept up in the excitement without a clear strategy.
Planning and education
It is critical to bring all stakeholders on board through education and training on the fundamental building blocks of data and AI. This involves understanding what’s accessible in the market and differentiating between various AI technologies. Executive buy-in is crucial, and by planning for internal process outcomes first, organisations can better position themselves to achieve meaningful outcomes in the future.
Stagger the roll out
Don’t bite off more than you can chew! Trying to deploy a complex AI solution to the entire organisation is asking for trouble. It is better to identify early adopter departments where specific AI pilots and proofs of concept can be introduced and their value measured. Eventually, you might establish an AI assistant studio to develop dedicated AI tools for each use case according to individual needs.
Embrace change
People are often wary of change, particularly change with such far reaching implications in terms of how we work. Clear communication, training, and ongoing support will all help reassure employees who fear being left behind.
Data and AI
In the context of data and AI, the perspective shifts somewhat. Most organisations already have policies in place for public cloud adoption. However, the approach to AI and data must be more nuanced, given the vast potential of the technology involved. It is not just about establishing a policy, it’s about engaging in conversations that drive actionable insights and outcomes.
That means planning data and AI use for the next eighteen months or risking being left behind. Even though some of the benefits of AI will not materialise for years, now is the time to start planning and getting the right foundations in place. But remember to be flexible: the industry is so dynamic and fast-paced that long term plans can soon prove out of date.
Exponential advancement
This brings us neatly to how rapidly AI is evolving, creating an ever-growing gap between organisations that have climbed on board the AI express and those left behind. Leaders must ensure their businesses fall into the former category by beginning with the augmentation of existing processes, tools, and ways of working. By integrating AI into these areas, organisations can start to see gains that will later translate into positive customer outcomes.
Infrastructure readiness
One of the fundamental questions IT decision makers need to ask is whether their infrastructure and critical systems are modern and capable enough to support AI capabilities. Seeing opportunities is one thing but realising them requires a solid foundation. Without the necessary infrastructure, even the best AI strategies will falter.
Policy and governance
Governance plays a pivotal role in AI deployment because organisations need to have a well-defined, robust policy framework to deal with all manner of potential pitfalls, such as data privacy concerns. Consulting services can help establish balanced policies that enable innovation without stifling it. It is also worth noting in this context that your data platforms and data foundations must be tolerant of the level of data quality needed to drive trustworthy decision making. If you don’t address underlying data quality problems, you will struggle to get the recommendations and value from the AI service.
The overall message is clear: now is the time to get on board with AI. Begin conversations that will enable the integration of AI into your operations but be careful not to take on too much, too soon. A balanced approach, which considers current capabilities and future requirements, will be critical to success.
About the Author
Sandy Kahrod, Modern Work Product Manager at Six Degrees. Six Degrees is a leading secure, integrated cloud services provider. We protect UK organisations and help them thrive in the cloud by giving them secure platforms to innovate and grow. We believe success lies in harnessing a truly diverse and inclusive culture. We put our exceptional people in a position to succeed, and along with our robust capabilities and strategic vendor partnerships this enables us to support customers on their digital transformation journeys regardless of their maturity, with the goal of enabling them to operate effectively and securely in the cloud. We’ve aligned all our services to allow customers to navigate the complexities they face today – enabling them to solve their digital transformation challenges and succeed as businesses.
