Though it may seem like AI has been around for years and that we already have a good understanding of its capabilities, the reality is more complex. The security industry has long used AI in the form of video analytics, but other industries are just beginning their AI journeys, enticed by the promise of new efficiencies and advanced capabilities.
Every organization, regardless of industry or customer base, appears to be pursuing AI in some form. But many are still grappling with a fundamental question: What does AI actually do for organizations today? What are the real benefits and, perhaps more importantly, what potential long-term risks are organizations taking on?
In fact, customer concerns are rising. One survey found that 63 percent of customers are concerned about potential ethics issues with AI tools, including bias and discrimination, and more than 75 percent are concerned about AI producing inaccurate or misleading information.
The AI technology sector is still maturing, and that evolution is likely to continue for years to come. But that doesn’t mean organizations should wait on the sidelines for the ethical dust to settle. In fact, now is the time to thoughtfully engage with AI. The priority should be to assess opportunities, evaluate risks and ensure that when AI is used, it is built upon a solid ethical foundation — one that supports responsible innovation and assuages customer concerns. At the same time, the speed of AI development can bring those ethical challenges to the forefront, making it more important than ever to choose the right technology partners to navigate the journey with you.
How to Implement AI Responsibly
- Define clear business use cases.
- Assess risks to operations, compliance and customers.
- Prioritize fairness, transparency and privacy.
- Establish governance and ethical frameworks early.
- Choose technology partners who share your values.
AI Means New Opportunities – and New Risks
One widely accepted truth is that AI has enormous potential to create new business opportunities. With these opportunities come new kinds of risk, however, and organizations must move forward with intention and care.
To tap into AI’s full potential, organizations first need to understand the exact problem they’re trying to solve. Is the goal to optimize workflows through automation? Improve customer service? Enhance data analysis? Once you’ve clearly defined the use case, the next step is to assess what could go wrong. What happens if an AI-automated process fails? How would that impact operations, customers or compliance? Are the risks external, internal or both? By conducting this thorough, nuanced analysis, organizations can make informed decisions about which AI tools to deploy and with which vendors or partners.
A good example of this is facial recognition technology. Although early discussions of facial recognition often centered around ethical concerns, the technology has evolved over time to become a useful and accepted tool when deployed responsibly and in the proper context. This shift didn’t happen by chance — it occurred because developers, regulators, and end-users began to approach it with greater nuance. Privacy laws have also helped to create clear boundaries, and the video surveillance market has shifted to place a greater emphasis on responsible use. Transparency and human oversight are important, and today’s providers increasingly recognize that.
Building on a Regulated and Responsible Foundation
For responsible AI deployment to succeed, it must contain a solid ethical and technological premise. Like the AI technologies themselves, ethical frameworks and regulations represent both an opportunity and a challenge.
The broader conversation around responsible AI is still evolving, and society has yet to reach consensus on what ethical AI should look like. But that doesn’t mean individual organizations can afford to wait. Internal discussions should start now, defining what ethical AI means for your team, what your limits are and how you plan to ensure compliance and transparency.
Ethical challenges range from biased decision-making and unreliable predictions to privacy violations and legal risks. Technologies like facial recognition, behavioral monitoring and predictive analytics can all raise complex questions about consent, data use and fairness. These concerns can’t be fully solved with one regulation or policy. But by facing them head-on, organizations can turn potential pitfalls into opportunities for leadership and innovation.
For instance, AI-enabled facial recognition is becoming more common across the globe, particularly in access control applications. The leaders in this space are those that are communicative and transparent about how these sensitive technologies work and how privacy is protected, with many leaders offering opt-in options for solutions like these to foster trust and maintain ethical technology use.
Organizations that begin considering responsible AI practices early in the development process are better positioned to manage concerns proactively. By aiming to prioritize fairness, transparency and data privacy from the start, rather than reacting after the fact, they create stronger foundations for long-term success. In my own experience, this also lays helpful groundwork for later steps, such as creating governance practices and review boards to address new AI developments.
One example is the introduction of the AI Act in Europe. By jumping on it early and using the Act as a guideline to shape the way forward even before all of the provisions become mandatory, organizations will be better prepared to direct product roadmaps to align with the coming legislation. Additionally, by establishing the framework and positioning early, organizations will rise as proactive AI leaders, allowing them to guide other organizations and customers through what’s poised to come next.
Partnering With Purpose
Once your organization has taken the time to look inward, the next step is to project that clarity outward. Today’s businesses can benefit from having a clear point of view on AI, ideally supported by thoughtful reflection and planning around use cases and ethics. Not every organization needs a fully documented ethical framework, but it’s important to be comfortable discussing the topic with potential partners and customers.
Armed with this, you can evaluate potential partners like developers, integrators and vendors, not only on technological merit but on shared values. If a partner aligns with your stance on ethics, it becomes much easier to build a trusted, long-term relationship.
Transparency is at the heart of this process. Organizations that are open about their AI ethics not only attract better-aligned partners, but they also gain internal and external trust. This isn’t just about compliance. It’s about building credibility, mitigating future issues and fostering innovation on a reliable, values-driven platform. The AI ecosystem is moving fast, but speed doesn’t need to come at the cost of responsibility. In fact, the best organizations will be those that balance both.
Turning Excitement Into Responsible Action
AI continues to develop as a dynamic, evolving field still very much in its hype cycle, creating opportunities for organizations, especially those ready to move quickly and carefully. Organizations shouldn’t be afraid to deploy AI, but they should do so thoughtfully, strategically and ethically. That means knowing your goals, understanding your risks, building a strong internal point-of-view and selecting partners who share your values.
The challenges are real, but so are the opportunities. And for organizations that choose to engage responsibly, AI offers not just a competitive advantage, but a chance to lead the way toward a smarter, more ethical digital future.
