In the evolving business landscape, organizations are relentlessly seeking ways to improve productivity, gain deeper insights from data, personalize end-user experiences and automate repetitive processes. As a result, many of your customers are likely hoping that integrating Artificial Intelligence (AI) will help them master these challenges effectively.

It’s November 2024 and I think it is safe to say, AI is officially everywhere. People are talking about it in cafés worldwide. So are your kids. Or your parents. Or grandparents. It may have been integral to your last car buying experience and has been used as a recommendation engine by your at-home/connected devices that hear you and want to improve your life by recommending products they think you need. It is pervasive and getting more so every day.

In the modern digital landscape, data grows at an astonishing rate. Mid-sized enterprises struggle to manage its volume and velocity, let alone its value. Today’s complex data environments must span hybrid and multicloud setups. And as transformative technologies like generative AI (GenAI) matter more to business operations, they must manage skyrocketing demand for sophisticated, flexible and scalable data solutions.

As technology evolves, the skills gap within IT departments continues to widen. New technologies are being adopted more quickly to keep pace with business changes, necessitating a constant update of skills. Yet, fully outsourcing these skills isn’t always the solution, as they are a core part of any IT organization. To effectively address this issue, we need a strategy that focuses on continually closing the skills gap.

As we transition into the next era of information technology, organizations face increasing pressure to deliver value to customers more rapidly. As well as higher quality, flexible access to data and applications and uncompromised security. Concurrently, they must manage growing complexity, including increasingly distributed hybrid cloud architectures and data sprawl – and accompanying costs – in order to remain competitive.

Organizations today face a myriad of risks that can affect their operations, reputation and bottom line. Prime among them are the existential threats to your data, including infrastructure risks and data risks. Comprehensive data governance solutions enable you to address both your infrastructure and data risk to build a resilient and secure environment that supports your operations and protects your valuable data assets.

Enterprise computing goes through constant cycles of reinvention, often driven by the arrival of an innovation with the potential to change everything. As a service business models and GenAI are both great examples. As anyone in this space can attest, the pace of change can age you quickly. But at the same time, it’s what makes the business so exciting. And dare I say, it’s what keeps everyone in it young. It’s a bit of a conundrum if you think about it.

Businesses face an ever-growing challenge: how to protect and manage their most valuable asset – their data. As organizations scale and digital transformation accelerates, the volume generated daily is staggering. IDC predicts that the global datasphere will grow to 175 zettabytes by 2025, requiring a substantial increase in storage capacity across the industry.