Technology

‘Your scientists were so preoccupied with whether they could, they didn’t stop to think if they should’. While this famous line from Jurassic Park is a poignant reminder of the dangers of unchecked ambition, it can also be applied to today’s rapidly evolving and fragmented AI landscape.

The mainstream availability of AI has compounded issues with shadow IT, as employees increasingly sidestep governance to deploy powerful, self-service AI tools. In this environment, many businesses are faced with how to manage the element of control when unmanaged AI systems start making critical business decisions based on fragmented, unverified data.

Like John Hammond’s ambitious yet doomed theme park, some organizations are now creating something powerful without fully understanding the risks or having proper containment measures in place.

It’s become a business imperative to find ways to ensure AI-ready data is trusted, compliant, and seamlessly connected. Here we explore the unintended consequences of AI-driven shadow IT and why businesses need a structured approach to data management to avoid costly mistakes.

The rise of AI-powered shadow IT

Shadow IT is not a new challenge, but AI takes it to a new level. With so many generative tools now readily available, employees can solve problems, generate content, or make recommendations at speed. This happens often without needing any technical expertise or approval.

This speed is both a blessing and a risk. In their enthusiasm to experiment and move fast, teams often pull data from disparate sources, bypassing enterprise-grade controls in favor of quick, isolated fixes. Over time, these short-term solutions accumulate, and organizations are left with a patchwork of systems, models and insights that don’t speak the same language.

The risk isn’t just that teams are duplicating efforts or misinterpreting data. Business-critical decisions affecting customers, supply chains, product development and strategic direction are increasingly being made based on unverified siloed information. When AI systems operating on flawed data foundations make recommendations that influence growth strategies, the potential for bias or error multiplies exponentially.

Unify and trust your data

The antidote to this growing risk is not to clamp down on experimentation. It’s to build the right data foundation, one that supports innovation while maintaining context and integrity.

This means giving employees access to high-quality, AI-ready data from across the business. It’s essential to build one harmonized layer that connects all business AI applications and ensures that everyone from developers to decision-makers can rely on a single source of truth.

This foundation keeps context intact, so the entire business can see where, how, when and why data was produced, building trust and accurately informing decisions. When data is unified, it also supports regulatory demands and keeps the business agile to future compliance requirements.

The cost of siloed data and duplicated spend

There’s a significant cost benefit to this too. When growth is the unanimous business goal, organizations cannot afford to hemorrhage spend on an inefficient IT landscape.

It’s estimated that organizations today spend up to 50% of their IT budgets on data and analytics, with a significant portion of that going on attempts to harmonize disconnected data sources. Yet, despite these efforts, many businesses still lack a continuous, unified data layer that brings these sources together in a coherent, usable way.

That’s not just inefficient, it’s a missed opportunity. In the age of AI, the power of data lies not just in how much you have, but in how well it’s connected. Without a shared foundation, AI models risk drawing the wrong conclusions or being trained on outdated information.

This in turn leads to additional budgetary pressures. Businesses need to confidently scale AI across functions, knowing insights are accurate, secure and compliant.

From raw data to business outcomes

To move from raw data to real business outcomes, organizations need more than just infrastructure. They need a strategic approach to data and analytics that supports decision-making at every level.

This means combining new technologies with existing business processes to create enriched, curated data products that deliver meaningful value. It means equipping users with advanced analytics, benchmarking tools and AI-powered insights applications that can both interpret the data and recommend actions.

This strategic approach helps limit the spread of shadow IT by reducing the need for employees to seek out unapproved tools or shortcuts. By aligning data initiatives with established governance frameworks and cultural values, organizations can ensure consistency, compliance and trust in the data being used. At the same time, it creates space for innovation and agility, enabling teams to move quickly and confidently within a well-defined structure.

When done right, the benefits are clear: smarter decisions, faster responses and better outcomes across the board.

Creating a culture of AI confidence

Ultimately, the question businesses need to ask is not whether they’re prepared to use AI, but whether they’re ready to do it responsibly and reliably.

Readiness starts with a strong data foundation, ensuring that information is accurate, accessible and well-governed. It means empowering teams with tools and guidance to innovate responsibly, creating a culture where experimentation with the right tools is encouraged.

The lesson from Jurassic Park was not that innovation is dangerous. It’s that innovation without structure, without guardrails and without consideration of the bigger picture can quickly spiral out of control.

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This article was produced as part of TechRadarPro's Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro

Here are the answers for The New York Times Mini Crossword for Aug. 8

• OpenAI's GPT-5 debut included the reveal of a new integration that allows ChatGPT Pro users to link their Gmail, Google Calendar, and Google Contacts directly to the chatbot
• ChatGPT can summarize your day, create a schedule, and flag important emails
• Though an opt-in feature requiring user confirmation, privacy issues are likely to be raised

The spectacle of GPT-5 may have overshadowed some of OpenAI's other news during its livestream on Thursday, but the demonstration of ChatGPT's new ability to directly peruse and analyze a user's Google data caught my eye as a major moment in ChatGPT's development and OpenAI's battle for supremacy among AI chatbots.

The new feature enables ChatGPT users to connect the AI chatbot to their Gmail, Google Contacts, and Google Calendar data. The demo showed ChatGPT responding to a request to see a schedule of the following day by going through the user's calendar and email inbox, then rapidly compiling a complete and complex schedule, including important unread emails to respond to.

This may not sound like a breakthrough to anyone who’s already overwhelmed with their digital list of things to do, but ChatGPT sorting that information and putting it in front of you might actually lower your stress, at least judging by the demo.

It's easy to imagine an AI outline for your day, or a nudge to handle that still-unread message, reducing the mental workload by cutting out the tedious sorting and linking of scheduled events to relevant emails. You might say, “What’s on my plate today?” and see your calendar paired with that flagged email. That would mean no more toggling between Gmail and your calendar, squinting at what's urgent.

Further, the data could help ChatGPT learn more about you and your needs by reading the meeting invites you've sent, deadlines you've barely hit, and RSVPs you sent the second you got the invite. For now, this option is only available to ChatGPT Pro users, though OpenAI promised it would become more widely available soon.

ChatGPT won't sneak a peek at your messages

That said, the idea of handing over Gmail and Calendar data to ChatGPT might raise an eyebrow or two for good reason. Gmail could hold confirmation of doctor appointments and secret romantic rendezvous plans.

Don't worry about inadvertently sharing those details with ChatGPT, though. You'll need to opt in to link your accounts to ChatGPT and confirm actions before they occur, which will prevent any emails from being sent automatically.

Then again, there are plenty of smart scheduling bots and email add-ons that automatically pull event details or remind you about missed invites. But ChatGPT’s integration adds actual conversation to the mix. You don’t forward an email or set up complex rules of how the automated system should respond to certain family members. You just type in regular language, and it will act more like a human secretary.

Assuming you're okay with the concept, you can see how those who use Google and ChatGPT might value linking the two. Especially if you're not a fan of Google Gemini for one reason or another. You might long to have an AI chatbot connected to your Google account, but simply prefer ChatGPT to Gemini. OpenAI wants to give you that option.

If Google doesn't have an exclusive claim to linking your email and calendar to an AI chatbot, then OpenAI can hope to win out in other areas where it may feel it has the advantage, like the power of GPT-5. You just have to be okay with letting ChatGPT see which weddings you'll be attending in the next few months.

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