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By the end of 2020, an estimated six out of 10 businesses had already moved their workloads to the cloud, spurned to action by the COVID-19 pandemic. As IT investment continues to rebound through the pandemic, this figure will likely keep growing.

Yet despite the growing use of enterprise cloud, too many organizations continue to make basic, avoidable errors in their cloud migrations. These inevitably lead to spiraling costs, delays, a lack of alignment and mismatched levels of maturity across organizational units. A 2019 Fortinet study found that, after failing to achieve anticipated returns, 74 percent of companies have repatriated applications back on-premises after initially migrating them to the cloud – a mind-boggling, avoidable waste of both budgets and employee time.

Why does this happen? In my experience, IT decision-makers planning a cloud migration often believe that there are only two routes available to them. They think they can either move quickly, with minimal changes thereby saving money but sacrificing on precision and not taking advantage of the benefits cloud can provide. Or they think that their team can undertake a painstaking, resource-intensive planning and development process to modernize all their apps as they migrate. This route leads to better outcomes but is prohibitively slow and costly.

But these are not the only two options that are available. Enterprises can also look to harness the power of AI and automation, giving decision-makers the best of both worlds while maximizing efficiency and outcomes.

Here’s how:

Use AI to Discover “Unknown Unknowns”

Cloud migrations are notoriously complex. If you combine all instance types, storage options, availability zones and pricing plans from the major cloud vendors, there are currently more than 25 million available cloud configuration options. Not surprisingly, this makes the planning phase of a cloud migration a torturous process. AI can help organizations understand the complexity, anticipate potential pain points and avoid unexpected costs – thereby eliminating or at least significantly reducing delays and downtime.

Typically, AI-based cloud migration applications map thousands of data points from a customer’s environment, and correlate them to an optimum migration pattern. This task would take an experienced cloud expert weeks to complete, but can be executed by an algorithm in minutes. Even better, the AI gets smarter with each cloud migration, as it uses historical data to inform its conclusions.

What’s more, unlike a human cloud migration team, AI has fewer inherent biases and a flawless “memory,” helping migration teams maintain objectivity and consistency in their decision-making.

AI and ML tools can have the greatest impact in the planning phase of a cloud migration. If applied intelligently, they can be invaluable in ensuring your migration runbook is as accurate and precise as possible.

Be Mindful of Potential Drawbacks 

AI is not a panacea – at least not yet. The risk of relying too heavily on AI and ML tools when planning your cloud migration is that they might miss some important nuances. For instance, the unique quirks of an organization’s culture, the subtleties of its wider business objectives and fast-moving external market factors will not be picked up by AI or ML tools.

That is why it is important to always have an experienced cloud engineer involved in your migration project. AI and ML can certainly act as a guide, but a skilled team will bring the needed creativity and vitally important real-life experiences that are also part of the work.

Post-Migration: Uncover Modernization Opportunities with Automation 

When organizations migrate applications to the cloud, too often we see decision-makers adopting a “set it and forget it” mentality. This inevitably leads to resource mismanagement and over-provisioning, which negatively affects performance and ultimately can leave organizations spending more money than needed. Security and compliance gaps can also easily go undetected, leaving systems open to cyber-attacks and potential regulatory breaches.

As your organization continuously evolves to meet the changing demands of today’s world, your cloud infrastructure should also follow and evolve. AI and automation can help by monitoring your cloud estate in real-time and providing intelligent modernization and innovation recommendations, allowing you to best leverage the technologies at your disposal and gain competitive advantage in the market.

Overall, despite what many organizations initially assume, a lot of the challenges of cloud adoption are not technical. Instead, the real test is deciding on the right route to take for your migration. Using all the tools at your disposal – including AI and ML-based platforms, along with a savvy team of experts – gives you the greatest chance of success.

This blog was featured in EnterpriseAI.