## AI accelerates more than just developer productivity

Since the general availability of our [AI assistant in GitHub's support portal in February 2024](https://github.blog/news-insights/product-news/copilot-in-github-support-is-now-available/), 60% of the cases presented to it were resolved, with the majority being solved in under 7 minutes. This investment is part of GitHub's commitment to leveraging AI across the Software Development Lifecycle - including crucial moments when engineers need support! Let's take a look at how engineers at GitHub used AI within our support business to better serve our customers.

## How GitHub improved customer support with AI

__Primary goal__

-   Improve GitHub's customer support experience by leveraging automation powered by AI.

__Support Portal Reach__

-   GitHub serves a global community of over 100 million developers. GitHub's [support portal](https://support.github.com) assists an average of 178,000 customers each month with product and support-related questions.

__Key objectives__

-   Enhance responsiveness.

-   Increase customer satisfaction.

-   Allow the support team to focus on more complex and long standing issues.

__Specific focus__

Streamline the resolution of level 1 support queries by making known solutions easily discoverable, providing customers with a more direct and efficient route to resolution.

__What was done__

To achieve these objectives, we developed and implemented an AI-powered conversational assistant. This assistant is designed to autonomously address routine inquiries, providing immediate assistance and surfacing known solutions more effectively for our customers. The model is grounded to GitHub's extensive product documentation, helping ensure that the AI provides accurate and relevant guidance based on our existing knowledge bases. Our development and deployment process was underpinned by [Microsoft Responsible AI principles](https://www.microsoft.com/en-au/ai/responsible-ai?ef_id=_k_CjwKCAjw3P-2BhAEEiwA3yPhwB3LqV50_7LnWPLwGDTFbovX-xSKxgnIs_zXWcnpmt6HW0162H2wVRoCHbgQAvD_BwE_k_&OCID=AIDcmmgp5f6cxq_SEM__k_CjwKCAjw3P-2BhAEEiwA3yPhwB3LqV50_7LnWPLwGDTFbovX-xSKxgnIs_zXWcnpmt6HW0162H2wVRoCHbgQAvD_BwE_k_&gad_source=1&gclid=CjwKCAjw3P-2BhAEEiwA3yPhwB3LqV50_7LnWPLwGDTFbovX-xSKxgnIs_zXWcnpmt6HW0162H2wVRoCHbgQAvD_BwE)

By integrating AI into this process, we aimed to reduce the number of steps and overall process friction that customers often face, while simultaneously allowing our support team to apply their expertise to more complex cases that require human ingenuity and deeper investigation.

The AI-powered conversational assistant was seamlessly embedded into the support portal as a fully optional feature where customers could choose to interact with the assistant if they desired. Those who opted to engage with the AI-assistant received immediate assistance. Additionally, customers were encouraged to provide feedback on their experience, helping us continuously improve the tool and better serve their needs.

__Impact of the AI-assistant__

Since the [General Availability (GA) release in February 2024](https://github.blog/news-insights/product-news/copilot-in-github-support-is-now-available/), 60% of the cases presented to it were resolved, with the majority being solved in under 7 minutes. This is equivalent to over 20,000 customers having their problems solved through Generative AI.

By resolving these queries, the AI assistant has allowed our support team to focus on more complex customer questions, where their expertise can have the most impact. We have seen customer trust and satisfaction in the system grow through increased usage since general availability.

__Future implementations__

GitHub support's AI assistant has been deployed into Copilot chat on GitHub.com. [This capability](https://docs.github.com/en/enterprise-cloud@latest/copilot/using-github-copilot/asking-github-copilot-questions-in-githubcom#currently-available-skills) helps GitHub users access product & support related information whilst remaining within their workflow.

We are currently developing further AI capabilities tailored specifically for our internal support team, aiming to further enhance their ability to deliver exceptional customer service. This tool will provide intelligent suggestions, assist with routine task automation, and offer quick access to relevant information, enabling our support staff to manage their workflow more effectively and address complex inquiries with greater ease. We are also planning to expand the knowledge base for the AI-assistant and refine its response capabilities to better handle a wider range of inquiries.

## Insights Gained

__The power of tailored AI experiences__

Throughout the development and deployment of the AI assistant, one significant lesson learned was the importance of tailoring experiences. Our engineers discovered that by optimizing the AI assistant based on customer queries---through tailored responses and context-specific guidance---we could significantly enhance its relevance and effectiveness across a broad range of use cases. For instance, developers and admins often require different types of support, and we've built the system to adapt accordingly. By taking into account the size and complexity of the user, we enable the AI assistant to deliver personalized assistance that addresses the specific needs of each user.

__Expanding innovation beyond productivity__

Another key takeaway is the potential for AI to drive innovation beyond just enhancing productivity. We encourage engineers to experiment with AI, pushing the boundaries of what's possible. Consider new ways in which AI could be leveraged to achieve novel customer and business outcomes, such as creating more personalized customer experiences. By thinking creatively about the possibilities, engineers can support their organizations to unlock new value and opportunities that go beyond the traditional scope of support automation. This proactive approach to exploring the capabilities of AI not only enhances customer satisfaction but also positions your organization to lead in their respective fields, using AI as a powerful tool for innovation.

## How to enhance your organization with AI

Bring a customer-centric approach to engineering with AI:

1.  Identify a customer pain point that may benefit from the power of AI.

2.  Define the benefits you want to deliver to your customer and any disbenefits you want to avoid and evaluate different AI solutions to address the customer pain point. Ensure you plan for tracking customer feedback and whether the solution is achieving the desired benefits.

3.  __Customize and implement your AI solution.__ Based on your evaluation, consider an initial high-level architecture proposal. It can be useful to undertake a proof of concept (POC) to test your proposal for the likelihood of meeting the target benefits. If your POC is promising, move into building for production ensuring ongoing testing as you build and that you meet any of your internal development processes and requirements. Once you have finished development and completed any release activities required by the team/organization, deploy to a small number of customers for initial feedback.

4.  __Review and iterate.__ Regularly collect feedback from your customers and internal stakeholders and scale your deployment of the solution as you grow confidence. Use feedback to refine the solution continuously, enhancing its effectiveness and ensuring it continues to deliver value.

## Looking forward to the possibilities ahead for GitHub Support

As we continue to refine and expand the usage of AI in GitHub Support, we are excited about the broader possibilities it presents for enhancing various aspects of our services. The success of AI in handling level 1 support queries has demonstrated the potential of automation to not only improve responsiveness and customer satisfaction but also to empower our support team to tackle more complex challenges.

Looking ahead, we see significant opportunities to extend the capabilities of AI in the realm of customer success:

- __Product usage guidance.__ AI could be adapted to assist users in navigating and utilizing GitHub's features more effectively. By offering real-time guidance and tips based on user behavior and context, AI could enhance the overall user experience, helping customers unlock the full potential of our platform.
- __Support data analytics.__ We envision AI playing a crucial role in support data analytics, where it can help identify common issues, trends, and patterns. This data-driven approach can provide valuable insights to both our support and product development teams, leading to proactive improvements in our products and services that directly benefit our customers. We recently published a [blog post](https://github.blog/ai-and-ml/machine-learning/how-github-harnesses-ai-to-transform-customer-feedback-into-action/) on how we harness AI to transform customer feedback into action.
- __Training and onboarding.__ Beyond supporting the support team, AI can be instrumental in the training and onboarding of new team members across the organization. By providing instant access to a wealth of knowledge, best practices, and contextual guidance, AI can help new employees quickly become productive, accelerating their integration into the team.

In conclusion, AI gives engineers an unprecedented opportunity to enhance both customer and business outcomes in an organization. GitHub will continue to explore these possibilities and collaborate closely with developers, and customers to ensure that AI continues to evolve and meet the ever-changing needs. If you haven't yet, try GitHub's Support AI-assistant by visiting the GitHub Support Portal and entering your query in the search bar. We value your feedback and would love for you to be part of this exciting journey as we continue to improve how we serve our community.

Want to learn more about the strategic role of AI and other innovations at GitHub? Explore [Executive Insights](https://github.com/solutions/executive-insights) for more leadership perspectives and thought leadership on the future of technology and business.

Will you join the call to use AI to accelerate your organization's success? The journey ahead is full of potential, and we are excited to realize these opportunities together.

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[Microsoft FOSS Fund](https://github.com/microsoft/foss-fund) is one of the many ways the company supports the open source ecosystem that we all depend upon for so much. Every quarter the company's FOSS Fund typically awards $30,000 USD split across 1-5 projects in order of most-voted. Past recipients include [LLVM](https://llvm.org/), [Debian](https://www.debian.org/), [serde](https://github.com/SparcLab/OpenSERDES), [YAML](https://yaml.org/), [mermaid.js](https://mermaid.js.org/), and [NVDA (NonVisual Desktop Access)](https://www.nvaccess.org/). Projects have used the funding for everything from paying for security audits to hiring graphic designers to create logos.

In this article we'll explore:

-   How Microsoft taps employees to identify projects to fund

-   What you should consider when building your own open source funding program

Building bridges to the open source community
---------------------------------------------

The FOSS Fund, inspired by [Duane O'Brien](https://www.linkedin.com/in/duaneobrien/), was established by Microsoft's open source program office (OSPO) in 2019 and made its first sponsorships to open source projects in 2020.  Projects are identified through  employee nomination and voted on by employees who have contributed to open source in some way in the last few months. Microsoft is able to tap into the knowledge and passion employees have for their dependencies as both an opportunity to support those projects, but also to build awareness of impact, need and advocacy beyond any one project. Now Microsoft is one of many companies participating in the [FOSS Funders group](https://fossfunders.com/).

"Microsoft's FOSS Fund helps us build connections between Microsoft employees and open source communities," says Microsoft Open Source Programs Office Principal TPM Emma Irwin. "Being able to evaluate dependencies for sponsorship, contribution, or other opportunities is a competency like any other in engineering and has to be taught and practiced."

How Microsoft FOSS Fund works
-----------------------------

Any Microsoft employee can nominate a project used by Microsoft, but only employees who have contributed to open source in the last six months are eligible to vote on the winners. Around six thousand employees voted in the last round.

To be considered, a project must meet the following requirements:

-   Be used by Microsoft products and/or services.

-   Have an OSI-approved open source license.

-   Have a way to receive funds that our procurement and legal teams approve.

-   Have transparent governance about where and how funds are directed.

-   Not be owned, or primarily maintained by Microsoft employees.

Projects must have public facing details about how sponsorships are distributed, for example in the form of a FUNDING.yml file or in the GitHub Sponsors pane. The goal here is to ensure that the community is not surprised by the direction of funding.

Irwin says GitHub Sponsors is the preferred way to handle donations because it's already established as an accepted vendor, and makes it extremely easy to make payments. "We've heard from people at other companies that they prefer to use GitHub Sponsors when possible too," Irwin says. She emphasizes that while it's a preference, it is not a requirement: The Microsoft FOSS Fund has paid projects through fiscal sponsors like NumFocus, SFI, and other means.

Words of advice
---------------

Irwin says that other organizations looking to create their own funds for open source software should start by setting goals and identifying metrics that teach employees about their dependencies and ways of investing that actually help---be that contribution, sponsorship or beyond. "You need to think about, given your budget, how many different projects  you are able to sponsor and what metrics you should use to find them," Irwin says. "For example if you want to focus on sponsoring single maintainer projects even one sponsorship can make a huge difference and you might be able to do more of those."

Keep adjusting as you go. "Treat the whole process as a continual learning opportunity," she says. "Keep asking what problem or problems you're trying to solve and how the funding will help."

Irwin also emphasizes that investment in open source is a cycle, with no beginning or end - it's important to regularly evaluate the impact of  these efforts on the sustainability of your dependencies over time and to look for emerging needs. "FOSS Fund is a one-time award" she says. "Projects need ongoing contributions to be sustainable."

That means more companies stepping up to keep open source projects thriving, with upstream contributions and, yes, funding.

If you're ready to start sponsoring the open source projects you depend upon, or you're a maintainer looking for sponsorship, [sign-up for GitHub Sponsors today](https://github.com/sponsors).

Open source depends on the efforts of contributions from around the world. Millions of people pitch in to write code, provide support, draft documentation, plan events, and all the other tasks that keep projects moving.


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Whether you’re addressing an issue, iterating on a pull request, or bootstrapping a project, GitHub Copilot Workspace helps jumpstart your tasks by describing what you want in natural language.

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Join us for an exclusive look at GitHub’s latest innovations and upcoming product enhancements for Q4 2024. This roadmap webinar will spotlight the next wave of tools and features designed to redefine DevOps workflows, drive team productivity, and keep your organization at the forefront of development.

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