Around the world, many AI discussions are driven by business leaders who don’t have full oversight over their IT teams, which can lead to said teams facing intense pressure to deliver.
Enterprise AI adoption in East Africa depends not only on a willingness to explore this new technological frontier, but also on the necessary infrastructure, access to resources and existing capabilities to actually do so.
The truth is that this is not always the case, especially when AI adoption differs significantly from cloud adoption, even though the latter eventually enables and leads to the former.
Whether you are a large institution or a small-to-medium business with a minimal IT stack, the AI trend is an opportunity for you to get your house in order.
The goal should not only be to become AI-ready, but to enshrine and reinforce foundational capabilities, including platforms, technical skills and staff training.
To put it bluntly, how can you expect to become a leader in AI if your IT team is struggling to keep the lights on?
Always keep the essentials in mind
The buzz and excitement surrounding AI comes with a potential drawback, especially for IT teams and professionals. The rush to capitalise on the trend and immediately kickstart AI projects can draw attention and resources away from priorities that are ultimately essential for their success.
AI cannot be a top priority when teams are struggling to run disaster recovery, have not renewed backup subscriptions, or have not been exposed to AI training or upskilling courses.
East African enterprises need a secure and stable IT environment. Whether they’re building one from the ground up or retrofitting an existing one for new technology integrations, they need to ensure the following solutions are in place.
- Power: This might be an obvious one, but enterprises need an uninterruptible power supply (UPS) that guarantees system uptime in the event of power outages or disruptions (a day-to-day reality for many businesses across Africa).
- Network monitoring: Going beyond simple ping tests that confirm network traffic is reaching devices, enterprises need to implement monitoring solutions that encompass all network components, ranging from CPU and memory to disk space and fans.
- Security: Deploying solutions such as identity and access management (IAM), threat detection and response, and secure development environments, enterprises need to uphold their security posture and ensure all their data, applications and networks are protected.
- IT support: Accelerated digital transformation demands that enterprises have adequate human resources that are solely focused on that transformation. Dedicated teams also ensure that enterprises’ technology remains aligned with their long-term goals.
For many enterprises, all of these solutions and others will be taken care of thanks to agreements with their cloud service vendors. After all, the cloud is effectively outsourcing IT infrastructure and management to a trusted provider.
But while cloud services are often managed, AI projects demand in-house expertise and readiness. And the technology’s rapid advancement is shifting the types of roles and skill requirements companies need to hire for as they move to automate processes.
That is why, in addition to AI/ML-enabled platforms and services, enterprises should invest in training initiatives that prepare IT teams, upskilling them so that they’re not just ready to embrace AI, but also improve their overall ability to meet the digital needs of the business.
Automation: Your first big AI project
If the goal of enterprise AI is to take data, read it and translate it into a measurable outcome with minimal human input, then enterprises are already halfway to embracing AI by applying automation to their IT and organisational structures.
Like AI, automation, even simple use cases such as business process management (BPM) and robotic process automation (RPA), enable enterprises to increase their productivity and efficiency and lay the groundwork to deliver new insights.
Later on, enterprises can inject a dose of intelligence, combining AI capabilities to further streamline and scale decision-making across their organisations.
When creating new IT systems or retrofitting old ones, IT automation should be the first port of call, even before non-technical execs mention AI.
The ability to deploy and configure infrastructure and applications is a prerequisite for any AI project and speaks to a value offering similar to that of cloud computing. It creates immediate value and frees up IT teams to focus on more important projects, or projects that will create further value.
A conversation about foundations
East Africa, like the rest of the continent, is experiencing a surge of AI-propelled transformation, especially in Kenya, which leads alongside Nigeria and South Africa in making the technology part of their economy.
Many businesses may see the value of AI and want to accelerate projects, but that cannot happen without them having foundational systems and processes in place.
Businesses do not have to worry because they are not alone in addressing this. Through vendor collaboration and partnerships, those in the region can evaluate and align their infrastructure with evolving demands and acquire the capabilities needed to excel in an AI-powered future.
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