The imperative to implement AI effectively means leaders need to think strategically about the critical phases that could make or break their projects
Imagine the transformative power of deploying the right AI technology to enhance your company’s operations. The success of your AI proof of concept (POC) is not just a step forward, but a significant milestone. It’s a testament to your company’s potential for technological advancement and a promising glimpse of the substantial economic benefits that AI can unlock once fully integrated.
However, the journey from a successful POC to full-scale implementation is fraught with challenges. Many companies struggle with obstacles that often arise during IT migrations and conversions. Leaders need to be aware of the potential pitfalls and think strategically about the processes involved: these are critical phases that can make or break your AI integration.
Complex processes
Migration involves shifting data and/or software from one system to another – potentially in the form of a code, data, application, operating system, or cloud migration. Conversely, conversion refers to transforming an old IT system into a new or modified one. For example, legacy code, reports, workflows, and dashboards often hinder companies’ ability to upgrade their technology stack or switch to a new platform. This is frequently made more difficult because the original creators of these systems have long departed, and documentation is often missing. As a result, conversions and upgrades can become daunting, risky, time-consuming, and more costly than anticipated.
These challenges are not just technical hurdles; they can lead to project failure. Even delays and additional costs resulting from poor migration and conversion can negatively affect your AI initiative’s return on investment (ROI). If not managed properly, what began as a promising AI project can quickly spiral into a costly, resource-draining endeavor. This underscores the need for caution and vigilance in managing these processes.
The strategic imperative
While these challenges may appear formidable, they are not insurmountable. The key to overcoming them lies in embracing a strategic approach from the start. Thorough planning and execution are vital to ensure that your AI implementation project thrives and delivers the expected benefits, without unnecessary complications.
Think strategically Leaders often view IT migration and conversion for AI implementation as purely technical issues. However, this perspective is a misconception. Strategic thinking is crucial for successful AI implementation. Developing a comprehensive plan that anticipates and addresses all potential challenges is essential. This strategic mindset ensures that AI implementation is not just about deploying new technology, but also aligning it with broader business goals.
Thinking strategically is particularly important because the strategy, business, and finance teams must work together to support the plan adequately. For instance, financial planning must consider the costs associated with potential delays or unexpected issues during migration. By doing so, the company can avoid running out of budget mid-project, a common cause of failed implementations.
Prepare for the unknowns Experienced IT executives often know what challenges and bottlenecks to expect when implementing new technologies. However, they must also recognize that there will be “unknown unknowns” –challenges that are impossible to foresee. This element of unpredictability is perhaps the most daunting aspect of IT migrations and conversions.
However, rather than letting fear of the unknown deter progress, companies should view these challenges as opportunities for growth and learning. Preparing for the known and the unknown is critical to successful AI implementation. This is where teamwork, culture, and transparency in managing a strategic migration will ensure success. By fostering a culture of open communication and collaboration, companies can better anticipate and respond to unexpected challenges, reducing the risk of costly delays or failures.
A small step is a quantum leap forward The adage “divide and conquer” has never been more relevant than in the context of AI implementation. Delivering results in small, manageable chunks has numerous benefits. It allows end users to see what is coming and increases their confidence in – and acceptance of – forthcoming changes to their workflows and processes.
Gaining small wins also lowers risk. It builds the momentum needed to complete large, complex projects. Moreover, it is often better to have many small results that gradually reduce the probability of failure than to bet everything on a single, massive deployment. This approach mitigates risk and provides valuable opportunities for feedback and improvement at each stage of the implementation process.
Stop the sprawl As companies increasingly rely on technology solutions from external providers, they may find that, over time, they have amassed a long list of vendors. An unexpected consequence of this tech sprawl is the accumulation of extensive and elaborate middleware solutions to connect these disparate systems.
Managing vendor relationships and maintaining such complicated infrastructure can drain productivity and capital, making the technology ecosystem more challenging and inefficient.
To address this issue, companies should consider scaling back the number of vendor relationships and consolidating their systems. Working with technology vendors who deeply understand AI migrations and conversions can provide a more streamlined and efficient path to implementation. By reducing tech sprawl, companies can focus their resources on what matters most: successfully integrating AI into their operations to drive business value.
Why implementation matters
No matter how powerful an AI technology is, it will be ineffective for any company if it is not correctly implemented and deployed on its IT stacks. The migration and conversion phases are critical to ensuring that the AI technology functions as intended and delivers the expected benefits. Getting these phases right can reduce cost, time, and resources, opening up the pathways to successful AI implementation.
While the journey from AI proof of concept to full-scale implementation is challenging, it is manageable with the right approach. By thinking strategically, preparing for the unknowns, delivering incremental progress, and mitigating tech sprawl, companies can navigate the complexities of IT migrations and conversions and unlock the full potential of AI technology. This approach not only ensures the success of the AI project but also positions the company for sustained technological advancement and competitive success in the future.
Terence Tse, Mark Schlesinger and David Carle are co-founder and executive director, member of the board of advisors, and North America managing partner, respectively, at Nexus FrontierTech. David Carle is also partner in AI and data innovation at Capital Markets Advisor