Building the Guardrails of Artificial Intelligence in Enterprise
By Sascha Giese (pictured), Tech Evangelist, SolarWinds
“With great power comes great responsibility”. This popular proverb often comes to mind whenever I hear how business leaders plan to use Artificial Intelligence (AI) to supercharge the productivity and efficiency of their organization. AI holds the potential to transform businesses, but how many leaders have considered the responsibility involved in deploying it, AI’s true value and purpose within the business, and how to stop it from being misused in ways that could impact employees, customers, and the future of the organization?
Tough questions demand answers if businesses are to address the ethical concerns surrounding AI. With public perception of business AI usage being as mixed as it is, business leaders should thoughtfully consider the purpose and place that AI has in their business. Ignore the hype and instead focus on aligning AI’s vast capabilities with the needs of employees, customers, and business partners. Only then can AI be implemented meaningfully, ethically, and fairly, to benefit and enrich every individual that it touches.
It all starts with purpose. Here are some practical considerations for leaders looking to amplify the benefits of AI within their organizations.
Establish a purposeful vision for AI
Purpose is nothing without vision, and for AI implementations to be successful in delivering their purpose, leaders must set an end destination, an ideal state. Build your strategic vision for AI with people in mind – in what ways will AI realistically help employees, customers, and partners? Then involve the necessary stakeholders, from IT and other business functions, to devise a realistic plan for achieving those goals. This sends out a strong message: AI is here to stay, and we’re committed to using it in a purposeful, governed, and accountable way.
Make this entire process as transparent and public as possible to foster trust with employees, partners, and end customers. For employees, this vision-setting serves to clarify AI’s role in the company – not to replace them and their colleagues but as a tool to augment and empower them to reach their goals. For partners and customers, a purposeful AI vision is a roadmap that details how the business intends to use AI to elevate the quality of service offerings, tap into emerging opportunities, and protect the interests of everyone involved.
- Build a robust and responsible AI governance practice
To ensure AI implementations remain on track, a strong hand is required to guide its purpose. This role is best served by the principles of AI governance that seek to proactively manage the risks involved in AI usage through the use of sound policy, data frameworks, and usage best practices. With a particular focus on empathy, transparency, and accountability, robust AI governance is the only way to keep businesses on the straight and narrow path of using AI to serve the interests of the collective public, not just business bottom lines.
Who’s in charge of AI governance? Typically, every individual who’s involved in any shape or manner should be expected to uphold the principles of AI governance, but leadership and the board are especially accountable since they own the business vision for AI. Duly executed AI governance doesn’t just prevent misalignment on AI implementations and purposes; it is also instrumental in keeping the business accountable for how things can be improved and done better in the event the use of AI negatively impacts business employees or the customers they serve.
- Take a second look at your data policies
It’s no secret that AI and data are highly interconnected. AI algorithms require a sizable amount of data to learn, improve, and generate more data that can be used to improve the algorithm further. In this closed cycle, the impact of certain decisions is more profound – feed AI with the right data, and it can generate results that are accurate and equitable. Feed it poor data, and the result is inaccuracy, bias, and opinions that may prove detrimental to both the business and its customers.
Data policies will have to be adjusted for this new paradigm. Emphasis should be placed on why certain data sets are connected to an AI solution – what business value and outcomes are expected from efforts to build the algorithm with this data? Also consider who decides what data to use, who gets access to the data that AI creates, and their end goal with that data. This level of scrutiny and transparency is needed to keep everyone accountable to the end purpose outlined in the business’ vision for AI – and to minimize the long-term damage bad data decisions can cause to future AI implementations.
- Finally, consistently discuss and assess the value of AI
Implementation is only the beginning. Keep AI initiatives aligned to their stated purposes by consistently evaluating, assessing, and optimizing things over time. This is also an excellent opportunity to have honest conversations with users on the effectiveness of AI. For instance, dig deep into whether solutions like AIOps are truly alleviating the burden of critical but repetitive monitoring and remediation work for IT teams, or how effective AI tools for HR are in reducing administrative burden or supporting talent recruitment and retention.
Future possibilities are vast when it comes to AI, but only if leaders can set a clear purpose and path for the implementation, now. Those that succeed will find that AI isn’t just any tool – it’s a tool that will empower their people, customers, and partners to realize their own purpose and success, wherever they are.
