The Risks of AI Implementation

09/09/2025

The hottest topic in business right now is Artificial Intelligence. The major tech bros are tripping over each other, trying to pinch the best creators at the highest prices away from their competitors. Major corporations are eliminating thousands of jobs because they have AI doing sales, customer service, and who knows what else. And, every other CEO I have spoken with seems to have a terminal case of FOMO. In this rush to implement and get ahead I wonder if the risks from these new tools are being overlooked.

So, with a hint of irony, I asked ChatGPT an important question — "what are the major risks to organizations rushing to introduce AI into their business?" Here was the response:

1. Strategic & Business Risks

Misalignment with business goals – implementing AI for the sake of hype instead of solving real problems.
Wasted investment – deploying tools that don't scale, integrate, or produce measurable ROI.
Vendor lock-in – committing too quickly to proprietary platforms without evaluating long-term flexibility.

2. Data & Technology Risks

Poor data quality – AI trained on incomplete, biased, or messy data can generate unreliable outputs.
Integration challenges – rushed deployments may not align with existing systems, workflows, or security infrastructure.
Overreliance on unproven tools – adopting generative AI or automation tools without adequate testing can disrupt operations.

3. Ethical & Compliance Risks

Bias and discrimination – AI models can inadvertently amplify inequities in hiring, lending, promotions, etc.
Regulatory exposure – privacy laws (GDPR, CCPA, evolving AI regulations) may be violated if personal or sensitive data is mishandled.
Transparency issues – "black box" models can make it difficult to explain decisions to regulators, stakeholders, or customers.

4. Security Risks

Data leakage – sensitive corporate or customer data fed into AI tools can end up outside the organization's control.
Adversarial attacks – AI systems can be manipulated or tricked by malicious actors.
Shadow IT – employees experimenting with public AI tools without governance can expose the organization.

5. Workforce & Cultural Risks

Employee pushback – lack of communication about how AI will impact jobs can erode trust and morale.
Skill gaps – rushing in without training or change management leaves staff unprepared to use AI responsibly.
Ethical unease – workers and customers may resist AI adoption if they see it as careless or profit-driven.

6. Reputation Risks

Customer trust – misuse of AI (e.g., tone-deaf chatbots, discriminatory decisions) can damage brand credibility.
Public backlash – deploying AI in sensitive areas (like HR, healthcare, or finance) without safeguards can spark negative media or regulatory scrutiny.

Bottom line: The biggest risk isn't AI itself — it's adopting it without strategy, governance, and clear guardrails.

As with all tools, not knowing how you want to use the tool before using the tool will lead to unintended consequences. When these tools are rushed into use, the impact on real people can be devastating. Understanding and mitigating the risks laid out here is an important part of a well thought out strategy. Developing a well thought out people strategy that incorporates these new, extremely useful tools, is imperative for businesses of all size to not only survive but thrive in the era of AI.