Foreword: Artificial Intelligence and the New Generation of Technology Building Blocks

Over the past few years, I have been fortunate to discuss artificial intelligence (AI) with C-suite executives from the largest companies in the world, along with developers and entrepreneurs just getting started in this area. These interactions impressed on me how quickly the conversation is becoming commonplace for business executives, even though AI in business is still in its infancy. As you pick up this book, I hope you realize what an incredible time we live in and how transformative having computers that can mimic cognitive abilities will be in the coming years and decades. Digital transformation is becoming a commodity play as organizations shift into the cloud, and business leaders must plan for and utilize a new set of technology building blocks to help differentiate their companies. Of these, the single biggest impact, in my opinion, will come from AI.

When I entered the software industry over 25 years ago, everything we built revolved around three core elements: computing, storage, and networking, all of which were evolving at an incredible rate:

1. Computing - 286 to 386 to 486 to Pentium, and more
2. Storage - 5¼? floppy to 3½? floppy, to iOmega drives, to thumb drives, and more
3. Networking - corporate network to dial-up modem to DSL, to 2G, 3G, 4G, 5G, and more

The evolution of these building blocks created new computing infrastructure modes (client computing to client-server, to Internet, to cloud and mobile, to today's intelligent cloud and intelligent edge) that allowed technology to better support business and consumer needs. Core computing paradigms and the infrastructure models we all rely on have continued to advance over the past three decades, taking us on a journey in terms of how computer technology is used in business and in our personal lives. Today's conversations have shifted away from traditional technology infrastructures and onto digital transformation and what it means for each business and industry. While the backbone of digital transformation is based on computing, storage, and networking, the next generation is beginning with an entirely new set of building blocks.

These new elements consist of things we read about every day and use in various ways within our organizations: Internet of Things (IoT), blockchain, mixed reality, artificial intelligence, and at some point in the future, quantum computing. The next generation of employees will be natively familiar with these building blocks and be able to harness them to more broadly and dramatically redefine every industry. It is entirely possible that future changes will eclipse the advent of the PC, mobile, and the current round of cloud-driven digital transformation.

Although these building blocks are powerful, AI provides the most potential of any tool to impact businesses and industries. Unlike the other elements, which apply to clearly defined use patterns, AI can be leveraged in every area of the business. This includes product development, finance, operations, employee management, and supplier/partner/channel alignment. AI can be used to impact both top-line growth and bottom-line efficiencies and leveraged at any point in a business or product lifecycle. Given the breadth of opportunities and the importance of a balanced approach to your organization's AI journey, this book provides a critical reference for business leaders on how to think about your company's - as well as your personal - AI plan.

Each organization will undergo its own AI journey in line with its business strategy and needs. Much like the Internet when it first came along, the excitement and energy for AI is incredibly high and the long-term opportunities immense. Knowing that we are still in the beginning stages of real AI implementations allows us to be more thoughtful and prudent in how we approach this area. Furthermore, the tools and data needed for AI are also on their own journey and continue to evolve at an incredibly high rate.

This move toward production-ready AI is based on three core advancements:

1. Global-scale infrastructure - computing, storage, and networking at scale based on the cloud, which ultimately enables any developer or data scientist, anywhere on the planet, to work with the data and tools necessary to enable AI solutions.
2. Data - the growth of raw data, both machine- and device-driven (PCs, phones, IoT sensors, etc.), and human generated (web search, social media, etc.) provides the fuel for creating AI models.
3. Reusable algorithms - the advancement of reusable models or algorithms for basic cognitive functions (speech, understanding, vision, natural language processing, etc.) democratizes access to AI.

By combining these three elements at scale, any organization or developer can work with AI. Organizations can choose to work at the most fundamental levels creating their own models and algorithms or take advantage of prebuilt models or tools to build on. The challenge then becomes where to start and what to focus on.

Today, we are seeing a set of patterns start to emerge within organizations across a broad set of industries. These include:

• Virtual agents, which interact with employees, customers, and partners on behalf of a company. These agents can help answer questions, provide support, and become a proactive representative of your company and your brand over time.
• Ambient intelligence, which focuses on tracking people and objects in a physical space. In many ways, this is using AI to map activity in a physical space to a digital space, and then allowing actions on top of the digital graph. Many people will think about "pick up and go" retail shopping experiences as a prime example, but this pattern is also applicable to safety, manufacturing, construction scenarios, business meetings, and more.
• AI-assisting professionals, which can be used to help almost any professional be more effective. For example, they can help the finance department with forecasting, lawyers with writing contracts, sellers with opportunity mapping, and more. We also see AI assisting doctors in areas such as genomics and public health.
• Knowledge management, which takes a custom set of information (e.g., a company's knowledge base) and creates a custom graph that allows the data to be navigated much like the web today. People will get custom answers to their questions, versus a set of links to data. This is a powerful tool for businesses.
• Autonomous systems, which refer to self-driving cars but also to robotic process automation and network protection. Threats to a network can be hard to identify as they occur and the lag before responding can result in considerable damage. Having the network automatically respond as a threat is happening can minimize risk and free the team to focus on other tasks.

Although these patterns are evolving and do not apply to every business or industry, it is important to note that AI is being used across a variety of business scenarios. So, as a business leader, where do you start? The intent and power of this book are to help business leaders answer this and many other important questions. In this book, Rashed Haq leverages his 20-plus years of experience helping companies navigate large-scale AI and analytics transformations to help you plot your journey and identify where to spend your energy.

A few things to keep in mind as you read this book. The first is that data is the fuel for AI; without data there is no AI, so you must consider which unique data assets your organization has. Is that data accessible and well managed? Do you have a data pipeline for the future? And are you treating data like an asset in your business? The next thing to remember is AI is a tool, and like any other tool it should be applied in areas that help you differentiate as a company or business. Just because you can build a virtual agent, or a knowledge management system, does not mean you should. Will that work help you with your core differentiation? Where do you have unique skills around data, machine learning, or AI? Where should you combine your unique data and skills to enhance your organization's differentiation? At the same time, should you be looking for partners or software providers to infuse their solutions with AI, so you can focus your energy on the things you do uniquely? If you think you have new business opportunities based on AI or data, think about them carefully and whether you can effectively execute against them. Finally, what is your policy around AI and ethics? Have you thought about the questions you will be asked from employees, partners, and customers?

The AI opportunity is both real and a critical part of your current and future planning processes. At the same time, it is still a fast-moving space, and will evolve considerably in the next 5 to 10 years. That means it is critical as a business leader to understand the basics of what AI is, the opportunities it offers, and the right questions to ask your team and partners. This book provides you with the background you need to help you understand the broader AI journey and blaze your own path.

As you begin thinking more deeply about AI and your company's journey, keep this simple thought in mind: "It's too early to do everything . it's too late to do nothing" - so leverage this book to help you figure out where to start!

Steve Guggenheimer

Corporate Vice President for AI, Microsoft