About the Author

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About the Author

THOMAS H. DAVENPORT is the President’s Distinguished Professor of Information Technology and Management at Babson College, the co-founder of the International Institute for Analytics, a Fellow of the MIT Initiative for the Digital Economy, and a Senior Advisor to Deloitte Analytics. He has written or edited 20 books and over 250 print or digital articles for Harvard Business Review (HBR), Sloan Management Review, the Financial Times, and many other publications. He earned his PhD from Harvard University and has taught at the Harvard Business School, the University of Chicago, the Tuck School of Business, Boston University, and the University of Texas at Austin.

Also by Thomas H. Davenport

Competing on Analytics: Updated, with a New Introduction: The New Science of Winning (with Jeanne G. Harris), Harvard Business Review Press, © 2017, ISBN 978-1633693722.

Keeping Up with the Quants: Your Guide to Understanding and Using Analytics (with Jinho Kim), Harvard Business Review Press, © 2013, ISBN 978-1422187258.

Judgment Calls: Twelve Stories of Big Decisions and the Teams That Got Them Right (with Brook Manville), Harvard Business Review Press, © 2012, ISBN 978-1422158111.

Thinking for a Living: How to Get Better Performances and Results from Knowledge Workers, Harvard Business Review Press, © 2005, ISBN 978-1591394235.

Conclusion

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Conclusion

The world seems to be moving at an incredible pace nowadays. New technology trends pop up all of the time, such as cloud computing or cryptocurrency. Increasingly, the world is seeing a trend towards AI. From research to engineering, customer relations to the hospitality industry, it’s not hard to envision a world that will soon see every market and industry revolutionized by artificial intelligence—but we’re not there yet. The AI Advantage gives you a taste of what’s out there and what’s currently possible without exaggeration or unnecessary hype. Davenport provides a realistic look at what leading companies are doing to stay ahead of the curve in the tech department. If you want to get on board with this movement, why not start now? Put on your research cap, dive into The AI Advantage, and enter into the exciting world of AI.

“Artificial intelligence holds fantastic promise for extending the reach and range of human capabilities. A company with no AI capabilities is as foolish as a company with no internet presence, or one that insists on using only analog, paper-based business processes…the time for AI in the enterprise is here. If your company's direct competitors aren't already embracing it, disruptive startups will.”

If you’ve enjoyed our insights on Thomas H. Davenport’s The AI Advantage: How to Put the Artificial Intelligence Revolution to Work, we encourage you to access the other The AI Advantage assets in the Skillsoft library, or purchase the hard copy.

Insights—Embrace the AI Revolution

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Insights—Embrace the AI Revolution

Use AI to assist in operations

While AI may have a lot of uses for different jobs in different fields, it won’t be completely replacing jobs just yet. Rather, look for ways that AI can augment your workflow, speed up processes, or ease the burden of everyday tasks. A little help can go a long way.

Be realistic with your vision

While AI can produce fantastic results, it’s still not as advanced as many people might purport it to be. Aim for realistic and achievable solutions. Remember, the more powerful solutions are going to be costly and could be difficult to implement. Start with small projects if you’re new to AI initiatives.

Be strategic in your approach

Don’t just dive head first into a fancy new AI initiative. Build a strategy from the ground up, carefully considering all the factors involved. Make sure you have the right content and expertise on the project. Remember to collaborate with everyone involved to make sure they’re on board.

Research the different types of ai

AI is a burgeoning new field and the technologies are likely to be very different from what you’re normally used to. Make sure you have a basic understanding of the different AI technologies. You don’t need to understand the mechanics of how they work; focus more on what each type can do for your company.

use ai responsibly

AI is still a fledgling technology and, for now, still requires human monitoring and validation. This is especially true if your AI solution handles sensitive information or makes important decisions. You shouldn’t leave it all up to the machine. Make sure you have some oversight and correct errors as they arise.

Book Summary

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Book Summary

Understanding AI

Artificial intelligence is something of an umbrella term. It can be used to describe a range of different technologies and programs used for a variety of functions. On a small scale, one form of AI is a system that automates responses to customer queries. On a larger scale, you have robots that can carry out full conversations. Understanding the differences between the different technologies and how they can fulfill your goals should be your first step in planning an AI solution.

“Understanding the differences between the different technologies and how they can fulfill your goals should be your first step in planning an AI solution.”

AI Capabilities

According to the author, to better understand AI, you need to think more broadly about the topic. Don’t just think about specific AI methods or solutions but also consider what the end result of an AI solution would be. In other words, what the AI is actually doing or what it is capable of doing.

Davenport looks at the main three capabilities that most solutions provide:

Automation: AI is often used to complete structured and repetitive tasks. This can be advantageous; after all, machines can usually complete these types of tasks much faster than a human, and with more accuracy.

Insight: Many AI solutions are used to gain insight into different areas that might be impossible or painstaking for a human to achieve. For instance, machine learning algorithms can comb through thousands of records, perform calculations, and extract meaningful insights from data.

Engagement: AI can be used to engage with customers and employees without the need for human contact. This is similar to automation but it relies more on human oversight and has to be more complex to handle a wider variety of situations.

Some AI solutions offer a combination of automation, insight, and engagement. For instance, you could have an AI “help desk” that can engage and answer questions and then automate basic tasks based on what a customer requires.

AI Basics

Davenport notes that, contrary to popular belief, most of the AI solutions available today aren’t the flashy kind we often see in the movies. Rather, they’re more practical and can offer businesses untold benefits. Many industry leaders, such as Facebook, Amazon, and Google are already using AI in different capacities, for search suggestions or identifying customer buying patterns, for instance. Moreover, many companies are now creating ready-made AI solutions for purchase, making it easier to get into the field without having to develop a solution yourself.

To fully comprehend what AI is and how it can help you, you’re first going to need to understand the different types of AI that are available. The AI Advantage provides a breakdown of the main AI in use today:

Statistical machine learning uses complex algorithms to discern patterns from data. This can be used, for example, to identify or classify customers based on a list of attributes.

Deep learning uses algorithms based on the brain structure to recognize patterns. This can be used in image and voice recognition software to extract meaning.

Rules-based expert systems are a set of logical systems that follow a rule set given to them by human experts. These can be used by banks to provide customers with credit approval, for instance.

Robot process automation automates digital tasks and interfacing with systems. For instance, companies can automate processes such as replacing credit cards or validating online credentials.

Davenport notes that it’s important to dig deeper into the subject if you want to fully grasp what is out there and what is possible when using AI.

Developing a Strategy

Once you understand what AI is and what it can do for you, it’s time to start developing your strategy. For instance, you need to decide what type of solution you require and how it will integrate into your current environment. You also need to consider aspects such as cost and the benefits you hope to derive from whichever solution you opt for.

Developing Strategic Objectives

A good place to start is to identify what your aim is. According to the author, you need to figure out what problem you’re trying to fix or what area you’re trying to improve. Once you’ve identified the outcome you wish to achieve, you can make decisions about what solution you require or if it’s even feasible to undertake.

What if you’re having trouble deciding between the different areas? Davenport suggests taking a look at the situation from your customer’s perspective. So, which changes will most benefit the customer? You might be quick to jump to a solution, such as a chat bot that can help customers with frequently asked questions. But these aren’t perfect and can even deter customers, who may prefer engaging with a real person.

The author also advises you to put some thought into whether you need an internal or external change. An external change, like a chat bot, can be impressive but might not be that helpful unless done well. Some internal automation, on the other hand, may never be noticed by a customer but might speed up your entire process—and, ultimately, enhance the customer experience.

“Some internal automation, on the other hand, may never be noticed by a customer but might speed up your entire process—and, ultimately, enhance the customer experience.”

Aligning Your Strategies

When developing your AI strategy, you need to consider more than just the technologies you’ll use. Davenport notes that there are other factors that may determine whether your solution is a success. The most obvious consideration is cost. Remember, many good solutions will be expensive—and that’s without adding the hidden costs of implementation and time to transfer. The author highlights some other key areas that should be aligned properly for a successful AI solution:

Content: Most AI solutions require some kind of content to run on or learn from. For instance, customer data or large galleries of images. In some situations, you can use whatever information you already have stored. In other situations, you might need to start collecting the right data or consider outsourcing it.

Talent: Whatever solution you opt for, you need to have experts on hand to work on it and work through any issues that may arise. This is especially true if you plan on developing a solution in house. Of course, experts can also be outsourced.

Partnering and acquisition: If you do lack the talent in your own company to develop a strategy, it may be worth considering partnering with another company to develop this solution. Many bigger companies, which are not IT or AI focused, have also elected to acquire smaller AI-focused companies to develop solutions for them.

Ambition: Keep your ambitions realistic, especially if you’re new to the world of AI solutions. Radical transformations rarely work out so try to keep your projects small. Stay within your own realm of business as well. Start with smaller projects and grow from there.

Once you’ve developed a strategy, you can determine if the solution is viable. Davenport notes that you may find that the solution you’ve identified isn’t the right fit at that point. If so, it’s better to hold off until you’re ready.

Managing AI Responsibly

AI represents an exciting new world of possibilities but it’s not without its drawbacks. For instance, you need to consider its indirect impacts, such as how a new solution might affect an employee’s workload or responsibilities. AI can have many shortcomings if not managed properly. You will need to prepare for the possibility of setbacks on top of dealing with the change management that comes along with new AI solutions.

“You will need to prepare for the possibility of setbacks on top of dealing with the change management that comes along with new AI solutions.”

The Drawbacks of AI

Davenport acknowledges that although AI can be beneficial, it’s not without its shortcomings, especially in companies that rely on a lot of interaction with customers or users. AI isn’t perfect and you need to be careful, especially when handling things like sensitive customer or user information. The author also notes that many companies have had problems with putting too much faith in their AI systems. They don’t oversee their systems properly and problems arise when everything is left up to the machine. Ultimately, there’s still need for human input and human oversight.

Many machine learning solutions do their learning in an autonomous manner; so much so that sometimes it’s impossible for a human to understand how it comes to certain conclusions. Davenport notes that this isn’t a problem, in most cases, as long as it reaches the correct conclusions. However, sometimes AI can unintentionally develop a bias, and this can be damaging. In other words, the program learns to discriminate against certain users or groups, even though that was never the intention. In these situations, it’s important to be transparent with customers, stakeholders or end-users about what is going on and work to rectify the situation.

Change Management

To implement any AI solution successfully, you’ll need to perform change management. The AI Advantage explores the need to get everyone on board with the idea of a new technology. As the author observes, this is vital in order for the new solution to work. For instance, you should collaborate with employees, executives, and any other stakeholders who may be able to offer input into the types of solutions that are required.

“The AI Advantage explores the need to get everyone on board with the idea of a new technology. As the author observes, this is vital in order for the new solution to work.”

Of course, not everyone will be keen to embrace AI. Davenport notes that a common misconception is that AI will make humans redundant in the workplace. But this isn’t usually the case. If fact, AI usually only fills one task and doesn’t replace the entire job. AI is also not fool proof; there’s room for error, which means human oversight is needed to ensure optimum performance. So, in this way, AI is useful to supplement jobs, not replace them—something you should keep in mind when developing a viable solution.

Ultimately, you need to keep an open mind and work with the people around you to see how this new AI future can work for everyone. For instance, it could mean reclassifying an old job or focusing the job into more niche areas that the AI can’t handle.

Finally, Davenport notes that while AI initiatives might seem bold, new and exciting, the changes don’t hit people equally. For a successful transition to a new initiative, there are three main types of employees who are most important and who you should try to keep happy:

Experts: In order for your AI initiatives to work, you’ll require assistance from employees with knowledge in the area. They’re usually the ones training and maintaining the technology. With the new system in place, some of their previous tasks may be supplanted and they may feel put out by the changes. So, make sure they know they’re working with the new systems, not being replaced.

Decision makers: You are likely implementing AI systems to improve decision making, which can feel threatening to employees who have previously been responsible for these tasks. Again, stress that these changes are meant to augment their jobs, make them easier, rather than replace them.

Recalcitrant learners: Some people will be slow to adopt new things and others unwilling to learn about these new technologies. Make sure everyone’s on board and positive about the change; this makes them more likely to adopt the changes quickly.

Regardless of who you’re focusing on, it’s important to stress the benefits of the solution and work with the people involved to figure out how they can integrate and utilize the solutions to improve their work.

The AI Advantage

How to Put the Artificial Intelligence Revolution to Work

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Book by Thomas H. Davenport

Published by The MIT Press | © 2018

Synopsis

When most people think of artificial intelligence, or AI, they think of science fiction, futuristic robots, and advanced supercomputers. The reality is much less glamorous but also much more attainable. In today’s world, AI is being used in many ways across a multitude of fields, from sales to medicine to engineering. To keep up, companies need to find ways to integrate AI into their everyday lives for things like automating processes, handling customer queries, and performing complex analyses.

The key concepts of The AI Advantage can be distilled into the following ideas:

Educate yourself

There are different types of AI solutions, so you need to know which one is right for you. Leveraging an incorrect solution can do more harm than not embracing AI at all.

Develop a Strategy

Rushing into a new solution won’t get you the results you desire. You need a strategy around how you’re going to implement this new solution.

Augment your work

The biggest advantage of AI is the fact that it enhances your work. AI can be used to carry out menial or difficult tasks faster and more precisely than humans. Use this to your advantage.

Stay Grounded

AI can do some amazing work but it’s far from perfect so be realistic about what you expect from your AI solution.

Based on The AI Advantage: How to Put the Artificial Intelligence Revolution to Work by Thomas H. Davenport, we discuss how AI can be used to enhance workplace solutions. The author believes that AI can be used to achieve a competitive advantage. We share our interpretations of these ideas in the following pages.

About the Authors

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ANDREW BURGESS is a management consultant, author, and speaker with over 25 years’ experience. He is considered an authority on innovative and disruptive technologies including artificial intelligence and robotic process automation. Burgess is a former CTO who has run sourcing advisory firms and built automation practices, and now advises senior executives on creating value from AI.

Also by the Author

The Rise of Legal Services Outsourcing: Risk and Opportunity, A&C Black Business Information and Development, © 2014, ISBN 978-1472906397.

Conclusion

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Technology is evolving every day and is often seen as both a gift and a curse. We love the fact that it adds convenience to our lives, but at the same time it causes frustration when we don't always understand how it works. The Executive Guide to Artificial Intelligence provides readers with a new perspective on AI and the possibilities for successful integration of this new-age technology in organizations. Author Burgess takes a practical approach to this book, providing a methodical framework that examines how each AI capability works in business.

“This is a book for practitioners of AI, people who want to use AI to make their businesses more competitive, more innovative and more future-proof…That is the mission of this book: be as informed as possible about AI, but without getting dragged down by the technology, so that you can make the best decisions for your business. ”

If you’ve enjoyed our insights on Andrew Burgess' The Executive Guide to Artificial Intelligence: How to Identify and Implement Applications for AI in Your Organization, we encourage you to access the other The Executive Guide to Artificial Intelligence assets in the Skillsoft library, or purchase the hard copy.

Insights—Transform Your Organization With AI

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Receive external help

When adopting AI capabilities, chances are you’ll require help from outside the organization. Allow third party organizations to build the specific AI capability you require for your organization. For example, requesting the expertise of Google to provide speech recognition and NLU software.

Choose wisely

Don't fall into the trap of purchasing software that isn't compatible with your AI system. For example, you might not be able to upload an accredited piece of software, because your current system doesn't allow JavaScript. Learn more about the software by seeking advice from someone who is familiar with the technology.

Ensure a good fit

Choose a software company that fits the culture of your organization. This company should resonate with the values of your organization. Find out how the organization treats its customers by reading online forums. Also, if you believe in quality over quantity, ask satisfied consumers about the service.

Do your research

Before purchasing, do your homework. You don’t want to adopt new software that’s soon to be outdated. Thoroughly check the quality and release date of the technology. And seek advice from a reliable, knowledgeable person who’s familiar with IT. Lastly, it's good to know the type of hardware required to run the software, such as processor speed and memory.

Provide an opportunity

Give a newly-established company a chance. By enlisting the company as your supplier, the company may feel the need to provide even better discounts and service. It's also a good idea to spread the word to other potential clients so that you can maintain supplier benefits and maintain a good relationship with them.

Book Summary

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Evolve With Technology

Living in a digital age, we have unlimited access to technology and information. Technology has definitely made our lives easier—consider the advantages of smart phones, or the Internet—so why shouldn’t it to do the same for your business? Andrew Burgess provides insights into AI, including his AI capabilities framework, and associated technologies.

“You should always be ready for new developments in the technology. AI is always getting better—advances that we weren’t expecting for decades are suddenly with us, and you need to be informed and ready to bring those into your business if they are relevant.”

AI Defined

Most people don’t grasp the fundamental definition of AI so they view it as something to be afraid of. Based on the Oxford English Dictionary, Burgess defines artificial intelligence as, "The theory and development of computer systems able to perform tasks normally requiring human intelligence." This definition hints at why the advancement of technology is often accompanied by negativity and fear from the public; it's seen as an uncontrollable force that could leave humanity vulnerable. This idea is often realized in movies and video games, which sometimes exaggerate the idea that technology will become so advanced that it will enslave humanity and take over the world.

You might not even have realized it, but your first encounter with artificial intelligence dates to the simple voice recognition software on your smartphone. But don’t be misled by these seemingly basic forms of AI, or underestimate its worth. Ai is a technological force that can transform your organization and put you ahead of the competition.

A Blessing Or A Curse?

Depending on how it’s used, AI offers business both advantages and disadvantages. According to the author, the use of advanced technological systems can positively disrupt various business elements such as the business model and decision-making processes. And when used in conjunction with human power, AI has the potential to enhance worker efficiency. For example, an AI system can quickly collect electronic documentation, while you, the agent, focus on building a rapport with a client. However, it also has the potential to replace hard-working employees whose skills are redundant due to automated processes or machines that can perform their jobs more efficiently and with less overhead. For example, chat bots may soon replace workers in the customer support department, or AI can replace the duties of bank tellers.

Why Now?

While AI offers endless possibilities for development, it hasn't really taken off in the past due to various issues such as, integration problems. But according to the author, the common thinking amongst organizations and executives is that the time for AI usage is now. What’s contributed to this idea is the staggering increase in the amount of data being generated globally, every day. On average, the amount of data is doubling in size every two years. The author states that by 2020 there’ll be 44 zetabytes of data copied every year. This is significant because, more data equates to a higher demand for AI operations in organizations.

According to Burgess, companies like Google and Facebook rely on AI to function optimally, due to the copious amount of data that requires processing and assessment. Essentially, he points out, the AI technology is a vehicle that needs fuel, which in this case is data.

Burgess explains that AI consumes data so that it can make sense of it. For example, the Google platform uses data such as user’s misspelled words from Internet search entries, to improve its spelling checker. Similarly, online stores collect dense data by observing trends and identifying which items are frequently bought by customers. Banks are also able to trace suspicious transactions based on data collected from your frequent banking activity—purchasing five televisions might seem strange if you don’t regularly make such purchases. These examples illustrate how companies can use AI to improve their business models and services to the public.

The author also claims that there are certain requirements when working with big data. First, the huge amount of data needs to be stored on servers, preferably at the cheapest price. Next, fast processors are needed to efficiently process large amount of data. Fast Internet is also important, such as 5G, to allow for data to be distributed between servers and devices.

Embrace AI Relationships

Artificial intelligence can do a lot, but it can't do everything. Even AI will sometimes require the help of other technology and humans to work efficiently. Andrew Burgess states that cloud computing—the availability of computer resources via the Internet—forms the basis for how AI systems operate today, because all data is stored on digital servers instead of a user's device. This allows for easy accessibility over the Internet. For example, cloud computing allows for a variety of functionality to be possible in organizations.

The combination of AI and cloud computing—referred to as cloud AI—is useful because it makes it possible to process large amounts of data easily. But cloud AI don’t only provide data storage, it also supports data processing. An example of data processing is when you use Google voice command to search for an item on your device.

The author outlines four main areas that make up the AI cloud:

Infrastructure. This refers to the servers and GPUs that train and run the AI systems.

Frameworks. This refers to development services used to build AI systems. Examples include ApacheMXNet, and TensorFlow.

Platforms. This is a resource used by developers to deploy and manage AI training. Generally, these developers have their own data sets but lack the required algorithms.

Services. This refers to pre-trained AI algorithms that are available to developers who lack both data sets and algorithms, and used to access a specific AI capability. For example, if you want to build NLU into your system, you could use Google's Parsey McParseFace.

Each of these capabilities serve a purpose and it depends on you if you want to integrate any one of them into your business model.

While useful, cloud AI also poses challenges to organizations. An example is the lengthy upload times to transfer data to the cloud. One solution, the author notes, is the use of the "Amazon snowmobile"— a physical truck onto which organizations load their data. The truck then downloads the data to the cloud servers at the Amazon headquarters.

“While useful, cloud AI also poses challenges to organizations.”

Another challenge is security. Storing data off-premises has a potential for risk because the data might contain sensitive information, such as a customer’s personal information, that could be accessed by unauthorized personnel.

Acknowledge Robotics

Besides the correlation between AI and the cloud, there's also AI and its relationship with robotics. According to the author, collaboration between AI and robotic process automation, or RPA, is another method for pushing organizations forward. RPA refers to software aimed at replicating the work performed by humans. For example, a robot can be used to perform insurance checks, payments, and invoice processing. Burgess also identifies other benefits of RPA in organizations:

robots are a cheaper form of labor and have the advantage of working 24/7

robots work just like humans but won't become ill, need a holiday, or request a raise

robots will always provide 100% quality when performing the task and their every action is recorded

There are various factors to consider when implementing RPA technology. The author outlines these, including understanding whether robots will require human aid to run, or run unassisted. Burgess also outlines some downfalls. For instance, will robots be able to apply a type of judgement or reason to their decision, similar to that of humans? Ultimately, it’s up to you to gauge the benefits versus the drawbacks of these newfangled approaches.

Realize The Power Of The Internet

In today's world, you won't find a device that isn't connected to the Internet. The author refers to the Internet of Things, or IoT, as all the devices—smart phones, consoles, cameras, televisions—that are connected to the Web. The relationship between AI and IoT devices is inseparable, he notes, because data is constantly transferred between devices and the Internet on a large scale. Some IoT devices in businesses include sensors in elevators, smart meters that manage water consumption, and field sensors that manage crop yields.

The possibilities for AI are endless, since AI can be programmed to mimic human-based tasks. However, there are some things AI is incapable of. And that's where crowd sourcing is implemented. The author defines crowd sourcing as AI receiving help from humans to complete certain tasks. For example, analyzing data from hand-written documents. People are often offered contracts for these micro tasks and are paid accordingly.

Finally, Burgess observes that technology, no matter how advanced, will always require the assistance of humans and vice versa. This symbiotic relationship is important for the co-existence of humans and technology, as they help each other daily.

“The possibilities for AI are endless, since AI can be programmed to mimic human-based tasks.”

A framework of AI capabilities

Advanced computer systems are the next big thing to help push organizations forward, but first understanding its functionality and implication within organizations needs to be considered.

Understand The AI Backbone

Burgess provides an AI framework that serves as a guideline to showcase the basic capabilities of AI in organizations. This framework is divided into eight categories:

Image recognition. How AI recognizes your photos/images. The first method is tagging—identifying different images such as a house, cat, or dog. Next, finding similar images using Google's Reverse Image Search. Last, AI can identify differences in pictures through medical imaging. The AI can identify the difference between a healthy and unhealthy x-ray scan, for instance.

Speech recognition. How AI interprets your voice commands. For example, Siri virtual assistant for iOS. Speech recognition software faces numerous challenges. For instance, the quality of data that requires processing may be affected by a noisy environment or poor connection. Language barriers and accents also pose a problem.

Search. How AI extracts data from a text, with the help of natural language processing, or NLP, to recognize word categories such as proper nouns.

Clustering. How AI groups similar data together. For example, the demographics among different customers and their similar purchases. The clustering capability uses predictive analysis. For instance, AI analyzes your purchases, and based on data from similar consumer purchases can provide you with offers.

NLU. Natural language understanding refers to how AI interprets words and its meaning. NLU acts as a translator between humans and technology. The goal of NLU is to determine the correct structure (syntax) and meaning (semantics) of words and sentences in data.

Optimization. How AI replicates human thought processing.For example, researchers program a robot to play video games to showcase its intelligence. Other examples include a GPS calculation of the fastest route home from work, or a robot tasked with figuring out how to unlock a door with a key.

Prediction. This is similar to clustering. The AI recommends which items you might enjoy based on similar purchases made by other consumers. For example, the suggestion of adding a screen protector since you've already added a smartphone to your online cart.

Understanding. How AI mimics the human brain, also known as Artificial General Intelligence, or AGI. The AI's intelligence is tested when required to select the correct buttons on the coffee machine in the correct sequence. Studies show that no AI system has passed this test because each AI capability is only allocated to one specific task. This means an AI programmed to process language won't possess problem-solving skills, for instance.

The author notes that these eight categories may not all be applicable to your business but at least one or two should correlate with your AI integration.

Take It For A Spin

You must test before you invest. There’s no sense purchasing or putting a product into production if you haven't identified possible limitations and areas of improvement. The same goes for an AI system. The author explores how developing a test version of your AI system can help with easier integration and discusses some of the obstacles you'll face when working with an AI system in your organization.

Start Somewhere

Creating an AI system is no easy feat. And once it’s created, you’re ready to test your assumptions about the system and verify your expected results. This is how you'll identify what needs to be improved upon.

The author points out that the size of your demo system depends on what you want to attain. For example, ask yourself how many AI capabilities you want to test. Burgess identifies five approaches you can use to test your AI system:

“There’s no sense purchasing or putting a product into production if you haven't identified possible limitations and areas of improvement.”

Proof of concept (POC). This demo software is discarded once the assumptions being tested have been proven.

Prototyping. This refers to building an AI capability and then testing the success of the capability. For example, image recognition software.

Minimum value product (MVP). This refers to when a piece of demo software is released to users to test its functionality. The feedback is used to improve the AI system.

Riskiest assumption test (RAT). This refers to testing the assumption which is least likely to be successful.

Pilot. This approach is similar to the MVP approach. However, a whole demo system is released to the users to be tested, instead of a single piece of software. It's also important to note that the pilot system needs to be fully functional.

It's essential that your selected approach fits your objective. For example, ask yourself if you really need to build a demo system, or which approach will provide you with the best results.

Recognize The Challenges

We've noted the capabilities of AI and ways in which it can improve your organization's efficiency. But it’s not all smooth sailing. The author discusses various challenges you may need to overcome when integrating AI into your organization:

Dealing with poor data

According to Burgess, the quality of data is based on its accuracy, or veracity, as well as how the data is used in a certain context. This is referred to as data fidelity. Poor data is evident in inconsistent data. For example, calcul

The Executive Guide to Artificial Intelligence

How to Identify and Implement Applications for AI in Your Organization

Book by Andrew Burgess

Published by Palgrave Macmillan | © 2018

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Synopsis

Have you heard the phrase artificial intelligence, or AI, bandied about but aren’t quite sure what it means? Are you battling to grasp the fundamentals of this futuristic technology and harness the power it offers? Are you keen to maintain your organization’s competitive advantage? You need a guide that demystifies machine intelligence, and allows you to leverage this capability to reach new heights.

The key concepts of The Executive Guide to Artificial Intelligence can be distilled into the following strategies:

invest in an artifical intelligence model

Harness the power of available technologies to make better business decisions. An AI model is invaluable when predicting customer behavior.

set your goals

Understanding what you want to achieve with your AI system is key to leveraging it correctly. To reach your destination, know where you're going and what you want to do.

create an ai blueprint

Identifying the best areas of opportunity in your organization will ensure that the AI system reaches its full potential. Focus on areas where an AI system can improve payment processing or technical support.

embrace change

A good way to positively disrupt your organization is to usher in a new AI system. This will create new jobs, but it also means existing jobs may become obsolete.

Based on The Executive Guide to Artificial Intelligence: How to Identify and Implement Applications for AI in Your Organization by Andrew Burgess, we discuss how organizations can use machine intelligence to increase their efficiency and productivity. The author provides insights into the core capabilities of artificial intelligence. We share our interpretations of these ideas in the following pages.