Artificial intelligence is a priority for both public and private sectors. Organizations are trying to keep pace with recent progress in technology, such as large language models (LLMs). But while AI enthusiasm is high, many are also aware of its possible risks.
A new study revealed 85% of IT leaders want to use AI in their organization’s IT and security operations, but 72% of leaders express worry about the potential negative impacts.
Since the AI -based tools can clearly help with automating various security and IT tasks, it may seem appealing to follow the industry’s perceived pressure to implement these tools. This raises the question, “Where should companies actually be applying this new technology?”
Prioritize Investing in People
Leaders should identify where AI can best help save time and effort for teams that do routine or low-level processing tasks in their jobs. This way, the human functions of their job can be improved even more.
When teams are not bogged down by menial tasks, they have more time to spend on skills development and problem solving.
This shifts them from viewing their jobs with a tactical perspective to a more strategic focus on tackling overarching processes or systemic issues. They can better evaluate where they need AI -driven automation versus existing tools that need manual intervention.
Investing in your people gives them more ownership and meaning in their jobs. It also increases their satisfaction for long-term retention. Employee burnout is already decreasing with 66% of IT teams saying that they’re not experiencing it at work and 40% feeling less burned out now than they did one year ago. By investing in AI -based tools that help productivity, IT leaders can enhance this trend and lower the number of employees who feel overworked or bored at work.
AI Cannot (Yet) Replace the Human Element in Cybersecurity
AI can seem like a quick fix to improve workflows and security decisions. But many companies are wrong to replace human decision-makers with new AI solutions in key business processes, especially in cybersecurity.
The (LLMs) – the latest AI breakthroughs AI – are only math formulas that guess the next word in a sequence. Relying on them to replace humans in key business processes that need human understanding can be risky. Instead, IT leaders should find ways to use AI to provide context for an existing human decision-making loop to see if it helps the human decide faster and easier. AI technology is then a tool that analyzes data better and helps to generate ideas, not the final judge.
The key to this strategy is that humans must check everything AI décide. Il est indispensable d’investir dans votre équipe et de la former pour s’assurer que tout ce que le modèle AI décide ou crée est contrôlé avec un degré de confiance élevé avant d’être mis en œuvre, afin d’éviter tout dommage potentiel.
Analyze, Then Invest
IT and security spending is growing, as 74% of IT leaders have a bigger budget than last year.
But more spending is not always better – it has to be used wisely. This applies to AI as well. AI hype can make you feel rushed, but you need to understand why you need it, if at all.
In the end, security leaders must evaluate their current resources and invest in their people first. This will help avoid waste and use existing optimizations before using AI systems. AI.
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Source: The Channel Pro Network
