Written by 12:02 Tech News Views: [tptn_views]

Taming the Artificial Intelligence Beast: 5 Reasons Why AI Deployment is Still a Challenge for Companies

Many would claim that we are currently in the golden age of Artificial Intelligence (AI). Bolstered by emerging technologies and breakthroughs beyond imagination, AI has indeed taken the world by storm. But contrasting with the perception of progress and advancement is the stark reality: AI deployment is far from easy. Although numerous companies have incorporated AI into their projects, a significant number still struggles to transit from the initial phases of AI integration.

The findings of a 2023 S&P Global survey shed light on this issue. It pinpoints that about half of these companies are stuck at the pilot or proof-of-concept stage. Why is the upgrade to a full-blown production scale proving difficult for these companies? While the reasons differ, we’ve broken down the top five challenges.

1. Acclimatization Issue: A New Environment to Adjust

One of the largest elephants in the room is the fundamental shift AI demands. As companies shift towards the AI landscape, employees and stakeholders must learn to adapt to a brand-new technological environment, often a daunting undertaking.

2. Skill Shortage: The Cry for Qualified Personnel

AI is a specialized field requiring competent professionals. Consequently, a scarcity of adequately skilled personnel to not only execute the project but also manage and oversee, it acts as a stumbling block for many companies.

3. Cost Factor: Bigger Budgets and Greater Risks

AI isn’t cheap. The cost associated with procuring the necessary hardware and software, together with the persistent need for maintenance and updates, can add up to a significant amount. This economic factor could deter smaller or more economically conscious companies from fully committing to AI.

4. Data Privacy: Navigating the Regulatory Minefield

AI thrives on data, a resource that is highly regulated due to privacy concerns. Navigating the regulatory minefield and ensuring compliance can prove challenging for companies working with AI, potentially slowing down deployment.

5. Proof of Concept: The Hefty Might of Reality

Finally, moving from a prototype to a full-scale production can be a looming task. Dodging the various pitfalls and unforeseen curveballs is inevitable, and most of these challenges tend to surface during the proof-of-concept stage, stalling companies in their tracks.

Artificial Intelligence, are we truly ready for you? The answer might still be under debate. But one thing is certain: equipping ourselves with a better understanding of the challenges that lie ahead will pave the way for a more seamless AI deployment process in the future.

Credit: BBC. TechCrunch, Reuters