- Generative AI has the potential to boost organizations' productivity and creativity outputs, but only if used responsibly.
- To reap the technology's full benefits, organizations must balance AI-enabled business transformation with strong governance.
- From using tools with built-in guardrails to establishing a governance plan, here are five ways organizations can use AI responsibly and effectively.
In recent years, businesses have integrated AI into nearly every facet of their operations. Across industries and departments, teams are using the technology to analyze large swaths of data, automate processes, and manage risk. But the next evolution of AI could unlock even greater levels of enterprise productivity and creativity.
Generative AI, which uses large language models and natural language processing techniques to create original content, could transform how businesses innovate.
However, these changes also come with a level of risk: To get the most out of generative AI, organizations must balance AI-enabled business transformation with strong governance practices. Here are five ways organizations can leverage generative AI responsibly and set themselves up for long-term AI success.
1. Understand your needs
Before deploying AI, organizations must understand where the technology can offer the most value. The answer to this question will likely differ depending on a company's mission and goals.
Consider starting with a gap assessment to evaluate current processes and opportunities to optimize them. If your company already has a strategic plan, assemble ideas from key stakeholders, including frontline employees who will use these tools every day, to determine how AI can help you achieve specific strategic goals.
Antony Cook, corporate vice president and deputy general counsel at Microsoft, said the technology's biggest potential benefit for businesses is accelerating process improvements.
"People are looking much more fundamentally at their process flows," he said. "They're looking at how they work. They're looking at the sorts of business processes that they run across their organizations — whether that's a contracting process, a compliance process, an advisory process, or a regulatory analysis process — and then they're starting to apply AI to help them get those jobs done."
A number of organizations are already using generative AI for these purposes — and are seeing promising results. The healthcare organization Providence, for example, used an AI-driven productivity tool based on Microsoft's Azure OpenAI Service to process and answer incoming patient calls faster, improving turnaround time by 35%.
2. Use generative AI tools with built-in guardrails and protections
To streamline generative AI adoption, most businesses will need to use third-party tools. When comparing solutions, Cook recommends investing in products that offer advanced security features and built-in copyright protections, especially if using generative AI for content creation.
Microsoft 365 Copilot, an AI-driven productivity tool that runs across the Microsoft 365 product suite, was developed to align with Microsoft's core AI principles. For example, the product features built-in guardrails such as intellectual property protections. Users of Copilot can rely on Microsoft's Copyright Commitment, which incorporates Microsoft's Responsible AI Standard focused on trust, transparency, and explainability of AI models. The Copyright Commitment also outlines Microsoft's duty to defend users against any copyright infringement claims as long as they didn't purposely infringe on the copyright and have the guardrail features turned on when they use Microsoft products.
Leveraging these protections when using Microsoft's solutions will decrease the likelihood of infringing copyrights when using generative AI.
"For the output that's generated from Copilot, we will stand behind the product and provide them with a defense against any infringement claim that may arise," Cook said.
These protections are critical, especially when a company enlists generative AI tools to help inform its business processes and decision-making.
PwC has integrated Azure OpenAI Service into its operations to enhance the efficiency of some processes. By leveraging Azure's powerful AI capabilities, PwC is optimizing tasks that traditionally required significant manual effort.
This is just one example of the business value responsible AI solutions can deliver.
3. Establish an AI governance plan
While generative AI's benefits outweigh its risks, AI still makes mistakes, such as producing inaccurate or unintended information. That's why it's important for organizations to ensure proper data governance, and to check that all of the documents available to the AI are up-to-date.
"Organizations are having to think much more centrally about how to make sure that the risk aspects of using the technology are managed within their own compliance environment," Cook said.
An effective risk framework will look slightly different for every organization, but at a baseline, your organization can start with AI principles centered around fairness, transparency, and accountability. These practices – along with inclusiveness, reliability and safety, and privacy and security — anchor Microsoft's Responsible AI Standard. Organizations can mirror some or all of these principles as they craft their own AI governance policies.
4. Foster a culture of continuous learning
As AI grows in both usage and popularity, successful adoption will require continuous learning on behalf of organizations and their employees. Microsoft Copilot features an intuitive interface where users can type in prompts to help with tasks such as drafting emails and creating documentation. But prompting takes practice and refinement. The best way to learn is to get comfortable testing and refining prompts. Organizational leaders can support staff by encouraging a culture of testing and continuous learning. For example, in-person workshops, on-demand video tutorials, and internal knowledge bases can all help employees get comfortable experimenting with AI.
5. Measure, learn, and adapt
Generative AI will continue to evolve. The use cases that serve your business today will likely change tomorrow, so continuously track and measure what's working and what isn't. Then, quickly adapt to unlock this technology's full potential.
Human feedback is a crucial part of this process. Generative AI is a transformative technology, but it's important to consider how it's used and where it gets its insights. Human oversight and feedback will be critical to assessing the output of generative AI systems and, ultimately, improving performance.
Like any technology, generative AI requires a solid implementation plan. By ensuring responsible and effective AI practices, your business can begin to maximize its benefits.
Learn more about Microsoft's Copyright Commitment here.
This post was created by Insider Studios with Microsoft.
