When ChatGPT launched in November 2022, even its creators at OpenAI didn’t expect what happened next. The generative AI tool went viral, attracting 100 million users in its first two months, and created a gold rush around Large Language Models.

To the average person, it felt like the stuff of movies – artificial intelligence was finally here to write your emails and do your homework. But to people within Avanade, the launch of ChatGPT was just a catalyst following years of AI work.

In fact, Avanade had been innovating together with Microsoft at the forefront of AI for nearly a decade. Following Microsoft’s investment in OpenAI in 2019, we had early access to emerging generative AI technologies and began spotting market signals of rapid advancement in foundational models.

We became our own first client for generative AI. As Microsoft innovated, we innovated.

As one of just 10 organizations in Microsoft’s Early Access Program (EAP) with OpenAI, we worked with over 100 clients on the earliest stages of their AI journeys. Fast forward 12 months, that figure has reached over 600 clients and we have been named Microsoft’s inaugural Global Business Transformation Partner of the Year for Copilot, plus further recognition as Best AI Consulting Service Provider at the AI Breakthrough Awards.

Read on to learn how we’re helping clients find measurable value from AI, how our experience as client zero makes this possible, and our top tips for adopting and scaling AI responsibly.

Customer experience

By generating relevant content, recommendations and solutions based on their customers’ needs, AI can help organizations create personalized and engaging customer experiences.

• We partnered with a major airline in Brazil to build a chatbot on AI that created an improved and accelerated service experience for more than 200,000 customers each month. Customer wait times have been reduced to nearly zero, retention rates have increased and employees responding to inquiries can do so more efficiently.
• Following promising pilots of generative AI solutions utilizing OpenAI, telecommunications company Telstra scaled up AI adoption. Over 80% of their employees agreed the technology has a positive impact on customer interactions.
• Leading banks are slashing the time it takes to process applications and seeing an uplift in customer satisfaction scores.

Employee experience

Work is becoming a team effort between people and AI. And we’re helping clients find new ways to empower their employees with generative AI tools.

• NISSIN FOODS Group created an AI chat solution that offered 4,000 employees capabilities such as text summarization, English translation, role-playing business negotiations and generating proposal ideas. Leaders expect it will help sales reps save up to 400 working hours per year while expanding their skills.
• Employees at pharmaceutical innovator Daiichi Sankyo are using the company’s new generative AI solution to develop ideas, assist with coding and content creation and contribute to learning and data analysis. Beyond improved output quality, it has also contributed to an enhanced workplace culture of digital transformation.
• Japanese automotive manufacturer DENSO saves employees hours of work by using AI to convert handwritten information and unstructured data into digital formats and structured data.
• U.K. recruitment agency PageGroup uses AI to spot patterns in data that we can’t see as humans. With this technology, recruiters have the information needed to get a better understanding of what’s going on in the job market to help people looking for work.

Responsible innovation

Real wins come when organizations move beyond automation into innovation. AI innovators are leaping ahead of competitors by reimagining the way things are done – taking advantage of how AI enables them to transform in ways not possible before.

• Duke Energy – one of the largest U.S. energy holding companies – is moving fast toward its ambition goal to achieve net-zero methane emissions by 2030. To do this, we partnered to develop an innovative, end-to-end solution built on Microsoft Azure and Microsoft Dynamics 365 that delivers new ways to detect, monitor and remediate methane emissions.
• SSE Renewables is the UK’s premier green company, with sustainability at the heart of its business. Together, we’ve created multiple AI-based solutions to protect the health and safety of the people and wildlife around SSE Renewables’ wind farms and hydroelectric installations.

Our research of 3,000 business leaders indicates that by 2025, 85% of business and IT leaders expect AI to increase revenue. We know AI is not a passing trend and is set to be a catalyst of growth for Avanade - and how we deliver for our clients.

By investing in our own AI transformation, we’ve taken several important steps to stay ahead of this opportunity. So what did these steps look like?

Leadership focus: We understand that AI – and generative AI in particular - transcends organizational boundaries. We could not just create an “AI department” in an isolated corner. This would touch every aspect of our business, and so we knew we needed executive-level leadership and focus.

An important step was appointing Florin Rotar as our first-ever Chief AI Officer in September 2023 and launching Avanade’s Global Center for AI – a hub that pulls together different parts of our business behind a clear AI strategy and vision.

Early adopter advantage: First came Microsoft Fabric, an end-to-end analytics and data platform that enables clients to better access, manage, govern and secure data. From day one, we had already developed a fluency that enabled us to launch the most comprehensive suite of Fabric solutions. Similarly, when Microsoft Copilot became generally available, we were ready to make an impact in market with six Microsoft 365 Copilot offerings. And we continue this momentum with AI tools and copilots that fit every need – from out-of-the-box industry solutions and extended AI models through to custom copilots and agent capabilities built on Microsoft Copilot Studio.

Upskilling: We invested to ensure that Avanade’s 60,000 professionals around the world had the resources, skills and support for an AI-first world. This included the launch of our School of AI to equip all Avanade employees – not just technologists – with valuable skills to navigate generative AI, responsible AI and prompt engineering. We’ve also leveraged this training material to help our clients roll out similar upskilling across their organizations.

Responsible AI: With the far-reaching potential of AI comes a great deal of responsibility. We’ve long had a digital ethics framework in place which helped us quickly extend it to include generative AI. Avanade continues to be a leader in this space, as part of The Microsoft Responsible AI Partner Initiative, which recognizes Microsoft partners that have established comprehensive AI practices.

Embracing disruption: We asked ourselves, “Are we going to be disrupted, or will we be the disruptors?” We implemented Disrupt Avanade, a program that empowers our people to spot ways AI can transform how we work. We distilled hundreds of ideas from across Avanade and move rapidly from experimentation to scale. To call out just two examples: our HR teams can now create job postings 87% faster and our marketing teams have an AI-powered tool which identifies patterns and themes from our customer data.

Quantifying value from AI: By putting generative AI tools in the hands of our people, we’ve been able to not only experience the value of AI, but quantify it. For example, early adopters of Microsoft Security Copilot reported saving up to 40% of their security analysts’ time on foundational tasks. With Copilot for M365, our people reported a 70% greater likelihood of fostering a creative approach to tasks. When using Copilot for Github, our developers saw a 50% uplift in successful code builds, along with up to 50% increased productivity – but more importantly over 90% reported feeling more fulfilled and enjoyed coding more. And when our sales team realized the potential of Copilot for Sales, Microsoft created a case study to learn from our experiences.

Our experience as client zero means we can share real-world experiences and first-hand learnings with you. AI is not as simple as turning on a switch and we anchor ourselves in four guiding principles.

First, AI value doesn’t start with technology. It starts with what’s most important: people. 63% of leaders recognize that their employees will need to learn new skills to make the most of generative AI. We found that giving attention to training and ongoing support –including tailored approaches –improved people’s effectiveness whilst increasing confidence levels by 26%. Without prioritizing these considerations, you run the risk of eroding employees’ confidence in AI. By showing how AI can help people reach their full potential, you build trust and adoption – the business outcomes follow naturally.

Second, don’t forget your strategic “why for AI.” The path to value is to map AI to the strategic objectives for your organization, and how it can bring competitive advantage in your industry. While most start with use cases that focus on optimization, those with bolder ambitions see more transformational value in the potential of AI to disrupt processes, functions, business models – and even industries themselves. This won’t happen overnight, and it’s important to cut through the hype by managing expectations for short-term versus longer-term value. And of course, there is no end state for AI – it demands rapid and regular realization of value.

Third, responsible AI is non-negotiable. We’ve seen a clear shift through 2024 in business and technology leaders getting serious about responsible AI policies and practices – coupled with new regulations such as the EU AI Act. When we talk to clients about AI adoption, our guidance is clear: don’t do it without a Responsible AI framework. If AI is to deliver on the promises it brings, we need people to trust it when processing their data, guiding important decisions, or streamlining critical workflows – otherwise its power starts to dissolve quickly. A framework for governance, including a combination of process, compliance, technology and training, enables you to move fast while upholding ethical standards.

Fourth, data matters and it’s crucial to be discerning about your technology ecosystem. No matter the use case for gen AI, quality data is a critical prerequisite – and most IT employees rank their data and analytics platform as among the top prioritize to scale AI. Differentiation also lies in adopting a strategic enterprise architecture mindset: will you consume existing solutions, extend them, or create entirely new ones? These choices can significantly impact costs, value and futureproofing, so it’s critical to make informed decisions.