AI Won't Eliminate Jobs or Businesses, But We Must Adapt

In these rapidly evolving and uncertain times, every company must tap into its unique strengths. AI has the potential to amplify these strengths, but only if organizations are willing to embrace it fully.

We've all witnessed technological shifts over the years. Think about how music consumption has transformed—from vinyl records to cassettes, then CDs, and now digital streaming. Or consider the evolution of telephony, from landlines to car phones, flip phones, BlackBerrys, and the smartphones we now rely on daily. While these changes have been significant, they've unfolded gradually.

In stark contrast, the emergence of artificial intelligence (AI) feels almost instantaneous. Despite AI's seven-decade history, OpenAI's introduction of generative AI has thrust us into what seems like a future straight out of science fiction. This sudden leap has left many executives grappling with when and how to embrace this new reality.

I urge leaders to approach this shift with confidence. As someone who appreciates the beauty of mathematics and the challenges of business, I find the AI-first world both exhilarating and transformative. AI's rapid integration into the workplace isn't about eliminating jobs; it's about disrupting outdated business models. Leaders must learn how to turn this disruption into a strategic advantage.

Today, the challenge with AI isn't about identifying use cases; it's about execution. A recent Lenovo survey of CIOs found that while 80% believe AI will significantly impact their businesses, integrating it presents substantial challenges.

The two primary hurdles are adoption speed and security concerns. With my company recently launching several AI-driven capabilities, I want to address the adoption challenge by sharing three key lessons from our experience.

1. AI for the Sake of AI Will Always Fail

When it comes to AI, it's vital to focus on problems that AI can solve more effectively than existing solutions. For example, in IT, Level 3 system engineers often spend considerable time diagnosing performance issues. Our team at Lakeside saw an opportunity to integrate a generative AI model to streamline this process, resulting in significant productivity gains.

Instead of developing our proprietary AI platform, we opted to use Microsoft's secure and trusted Azure AI platform as the foundation, infusing it with our proprietary IT data gathered over years of endpoint data collection.

Now, IT system engineers, who are already overwhelmed by the demands of managing constantly evolving IT environments, can ask the model questions in natural language. These AI-driven queries enhance our core product by integrating intelligent IT copilots, not replacing it.

2. You Must Get Your Data House in Order

As the leader of a company that's been in the IT data intelligence business for 27 years, I'm in a fortunate position as the AI transformation takes off. Data collection is at the heart of our business, but for companies struggling with data management, I would say that collecting vast amounts of data without a clear strategy is futile. You'll never be able to trust or fully understand the insights your data can provide if it isn't well-organized and labeled.

While 31% of enterprise leaders surveyed by TechTarget Enterprise Strategy Group prioritize "data insights" for generative AI, the same percentage cite "limited availability of quality data" as a significant challenge. High-quality data is crucial for ensuring that AI models produce reliable and relevant outputs.

To get your data house in order, identify redundant data sources, address data blind spots, and resolve conflicts arising from unintegrated systems—a common issue in organizations that have undergone mergers or acquisitions.

While the speed of AI adoption may be a priority for you or your CIO, it's essential to first take a step back and organize your data before forging ahead with your AI strategy.

3. Do Not Forget About Change Management

This final piece of advice is often overlooked. Having worked in high-growth startups, I know that user adoption is a frequent obstacle. Often, a CIO or CISO recognizes the value of a new tool, but the end user struggles to see its relevance in their daily workflow.

This is where business leaders need to communicate the benefits of new tools clearly and demonstrate how they will simplify and enhance the user’s work. Once users experience how AI can streamline their tasks and reduce digital clutter, there's no going back to the old, reactive ways of IT.

Whether it's integrating generative AI models into existing workflows to boost productivity or deploying machine learning for predictive analytics, IT leaders must prioritize change management across the organization.

A New Dimension in the Age of AI

The future shaped by AI is here. As I’ve previously emphasized, every company must unleash its superpower in these turbulent times. AI can enhance that superpower, but only if you open the door and invite it in.