A recent Gartner poll of over 2,500 executives, showed that 38% saw customer experience and retention as the primary purpose of their generative artificial intelligence (AI) investments. Significantly ahead of revenue growth (26%), cost optimization (17%) and business continuity (7%).
With that in mind, let’s look at the history of Microsoft’s commitment to AI and opportunities to infuse AI across the customer lifecycle. For completeness we’ll look at the breadth of AI offerings from Microsoft, not just generative AI (GenAI), as there is still very much a place for “traditional” AI.
While AI hit daily mainstream news at the end of 2022 with the public release of OpenAI ChatGPT, Microsoft’s commitment and investment in AI is not new. In an August 2023 interview with Fast Company Satya Nadella (Microsoft CEO) said
“What happened in the last five months, was work of the last 10 years.”
The fruits of this deep commitment are now being realised and released at pace thanks to a broad software, hardware and governance foundation that has been established.
Some key milestones in the Microsoft AI journey include:
Every step of the customer experience can be augmented with AI to provide more effective service delivery, more personalised and relevant content and ultimately experiences that drive greater loyalty and advocacy:–
Marketers are under more pressure than ever to simultaneously run many campaigns, reduce budgets and react to a rapidly changing consumer expectations.
Opportunities:
Microsoft Products and Capabilities: Dynamics 365 Marketing and Customer Insights Copilot, Designer and Bing Image Creator
With global economic challenges continuing, many organisations are seeing pressure on both growth and profits.
Opportunities:
Microsoft Products and Capabilities: Sales Copilot (formerly Viva Sales) for Dynamics 365 or Salesforce
Many service based organisations are facing staff shortages or significant staff turnover that lead to poor and/or inconsistent customer experiences.
Opportunities:
Microsoft Products and Capabilities: Dynamics 365 Customer Service Copilot, Power Virtual Agents — conversation boosters, generative answers and user authored plugins, Teams Premium, Nuance
Organisations with field workers/engineers have a tremendous opportunity to provide face-to-face personalised service in the customers home or business.
Opportunities:
Microsoft Products and Capabilities: Dynamics 365 Field Service Copilot
The recent pandemic and other geo-political and climate related events have shown how fragile supply chains can be.
Opportunities:
Microsoft Products and Capabilities: Copilot in Microsoft Supply Chain Center
Of course it is difficult for employees to provide exceptional customer experiences if they themselves have poor tools and data.
Opportunities:
Microsoft Products and Capabilities: Power Virtual Agents — conversation boosters, generative answers and user authored plugins, Microsoft 365 Copilot, Microsoft Syntex, Viva Copilot, Teams Premium
While the above provide many exciting opportunities, the real and enduring differentiation for brands can come through creative custom multi-modal scenarios built leveraging AI services across vision, images, speech, text, language, voice, search and decision making — grounded in the organisations own data.
Limited only by imagination, exciting opportunities exist to re-imagine existing experiences and create completely new ones.
Microsoft Products and Capabilities: Azure Open AI (GPT-4, ChatGPT, GPT-3.5, GPT-3, DALL-E, Codex), Azure Cognitive Services, Llama 2 on Azure, Semantic Kernel SDK
Increasingly Makers are an essential community in agile organisations, bringing to life innovations that in the past may never have received budget.
Opportunities:
Microsoft Products and Capabilities: Power Apps and Power Automate, AI Builder
While the opportunities to enhance customer experience with AI are exciting and the results can often seem magical, there are important areas to consider for success.
Firstly, and it may sound obvious, but customers are above all, human. Experiences we create, regardless of the technologies used, should treat customers with empathy and be cognisant of the emotional state of the customer in that moment. For instance, the emotional state of a customer calling their insurance company following a car accident is likely to be very different to that of a customer buying a luxury item.
Secondly, old adages still apply. In particular “Garbage in, garbage out”. AI is not magic and relies on the corner stone of data, quality data. For meaningful outputs, input data needs not only to be accurate but fresh, relevant, representative and unbiased. With that in mind, a key pre-requisite for a successful AI project is data analysis and preparation that also considers the genesis of the data to avoid privacy or compliance issues.
Finally, AI is imperfect. Important decisions and communications should continue to have human involvement so basic human values and your brand values are not offloaded to algorithms.
Microsoft have a deep commitment to responsible AI and a vision that AI is “built by humans for humans” — hence the theme in the product names of “Copilot”, not Auto Pilot.
In a CNBC interview on 16 May 2023, Satya Nadella said
“AI is already there at scale. Every news feed. Every sort of social media feed, search as we know of it before chat plus search, they are all on AI. If anything they are black boxes. I describe them as the autopilot era.
We are moving from the autopilot era of AI to the copilot era of AI. If anything, I feel yes it is moving fast, but moving fast in the right direction. Moving fast where humans are more in control. First of all, humans are in the loop versus being out of the loop.”
Microsoft Responsible AI principles cover fairness, inclusiveness, reliability & safety, transparency, accountability and data privacy & security. These principles also align with Microsoft’s commitment to harness AI as a vehicle to bring products and services to the one billion people around the world with disabilities.
To support the responsible AI endeavours, Microsoft uses Red Teaming, the approach of pretending to be an enemy and proactively hunt for failures, to probe not only AI security issues but also responsible AI outcomes.
In recent months, following the wave of GenAI announcements from Microsoft, the most common questions I’ve received are:
Q: Is my corporate data used to train Microsoft’s models?
A: No, Microsoft don’t use customer data to train models. Nor are customer prompts used for training.
Q: Are Copilots 100% factually correct?
A: No, hallucinations are possible due to the underlying nature of generative AI (Note: this problem is universal in GenAI models). A statistical approach, based on millions or billions of data points, is used to determine the next most appropriate word. Consequently, it’s essential humans are kept in the loop to validate outputs. Remember however, the nature of hallucinations, which often look genuine, can make them difficult to spot.
Q: What’s the difference between ChatGPT and Microsoft’s Copilots?
A: Microsoft’s Copilots provide context within the task being performed and ground both the prompt and response in the organisational data. This approach results in more relevant suggestions. More details on grounding can be found here.
Q: What about the risk of infringing the IP of authors and creators who may not have consented to their content being used in the training of foundational models?
A: With Microsoft’s Copilot Copyright Commitment, Microsoft says “if you are challenged on copyright grounds, we (Microsoft) will assume responsibility for the potential legal risks involved”. Of course, legal guidance should be sort and the customer must have used the guardrails and content filters built into the products.
The features released to date (described above) are a fraction of the Microsoft product roadmap. We will continue to see deep infusion of AI right across the Microsoft ecosystem in future product waves to further enhance both customer and employee experiences.
Microsoft’s AI research continues at pace across areas such as multi-modal large language models (MMLLM), the hardware to deliver and scale such immense models, AI noses for sensory experiences and situational intelligence to understand and act on the human world around us.
To find out more and understand how to start small and scale AI to enhance your customer and employee experiences, please reach out to me on LinkedIn.
Microsoft Artificial Intelligence enhancing Customer Experiences was originally published in Capgemini Microsoft Blog on Medium, where people are continuing the conversation by highlighting and responding to this story.