What is Artificial Intelligence?

Artificial intelligence is a collection of many different technologies that work together to enable machines to sense, understand, act and learn with human-like levels of intelligence.  Perhaps that's why everyone's definition of AI is different: AI isn't just one thing.

Technologies such as machine learning and natural language processing are part of the AI   landscape.  Each evolves in its own way, and when applied in conjunction with data, analytics and automation, can help businesses achieve their goals, whether it's improving customer service or improving customer service.  Optimize the supply chain.

Narrow (or "weak") AI

Some go further by defining artificial intelligence as "narrow" and "general" AI.  Most of what we experience in our daily lives is limited AI, performing a single task or a set of closely related tasks.  Examples:

Weather apps,Digital assistants

Software that analyzes data to optimize specific business performance

These systems are powerful, but the field is narrow: they focus on driving efficiency.  But, with the right application, finite AI has enormous transformative power and continues to influence the way we work and live around the world.

Normal (or "strong") AI

General AI is the kind you see in science fiction movies, where sentient machines mimic human intelligence, thinking strategically, abstractly, and creatively, and capable of performing a variety of complex tasks. 

 While machines can do some tasks better than humans (data processing, for example), this fully realized vision of general AI doesn't yet exist outside of the big screen.  This is why human-machine collaboration is so important: in today's world, artificial intelligence remains an extension of human capabilities, not a replacement.

Why is AI important?

Artificial intelligence has long been a topic of anticipation in popular and scientific culture, with its potential to transform business and the relationship between people and technology in general.  So why is the use of AI reaching critical mass today?

Due to the proliferation of data and the maturation of other innovations in cloud processing and computing power, the adoption of AI is growing faster than ever.  Businesses now have access to unprecedented amounts of data, including dark data they didn't even know they had until now.  This latent funding is a boon for the growth of AI.

A significant source of business value when done right

AI has long been considered a potential source of business innovation.  With the enablers already in place, organizations are beginning to see how AI can multiply their value.  Automation reduces costs and brings new levels of stability, speed and scalability to business processes;  In fact, some Accenture clients save up to 70% time.  However, AI's ability to drive growth is even more compelling.  Companies that successfully scale will see a 3x return on their AI investments compared to those stuck in the pilot phase.  Unsurprisingly, 84% of senior executives believe they need to use AI to achieve their growth goals.

Agility and competitive advantage

Artificial intelligence is not just about efficiency and making laborious tasks easier.  Using machine learning and deep learning, AI applications can learn from data and results, analyze new information from multiple sources, and adapt accordingly with a level of accuracy that is invaluable to companies.  (Product recommendations are a prime example.) This ability to self-learn and self-optimize means AI is constantly increasing the business benefits it generates.

In this way, AI can help businesses adapt quickly with a constant flow of information to deliver innovation and competitive advantage in an ever-disruptive world. 

When scaled, AI can become a key enabler of your strategic priorities and a key to survival: Three out of four senior executives believe that if AI doesn't scale in the next five years, they risk being excluded from it.  services.  Purely business.  Clearly, the stakes are high at the AI   level.

Benefits of AI

There are many ways to define artificial intelligence, but the most important conversation revolves around what AI allows you to do.

End-to-end efficiency: AI eliminates friction and improves analytics and resource utilization across your organization, resulting in significant cost reductions.  You can automate complex processes and reduce downtime by predicting maintenance needs.

Improved accuracy and decision making: AI augments human intelligence with rich analytics and pattern prediction capabilities to improve the quality, efficiency and creativity of employee decisions.

Smart Bidding: Because machines think differently than humans, they can quickly uncover market gaps and opportunities, helping you introduce new products, services, channels and business models with speed and quality never before possible.  It was not possible before.

Empowered employees: AI can solve mundane tasks while employees spend time on more fulfilling, high-value tasks.  By fundamentally changing the way work is done and increasing the role of people in growth, AI is expected to increase labor productivity.  Using AI can unlock the incredible potential of talent with disabilities, while helping all workers thrive.

Superior customer service: Continuous machine learning provides a constant stream of 360-degree customer insights for hyper-personalization.  From 24/7 chatbots to faster help desk routing, businesses can use AI to manage information in real time and deliver touch-based experiences that drive growth, retention and overall satisfaction.

AI can be used in many ways, but the current reality is that your AI strategy is your business strategy.  To maximize the return on your AI investments, identify your business priorities, then decide how AI can help you.

The future of AI

According to Accenture's report, AI: Built to Scale, 84% of business leaders believe they need to use AI to achieve their growth goals.  However, 76% admit to having trouble scaling AI in their business.  As of now, there are no plans to go from proof of concept to production and scale, a transition many struggle to make.  At this inflection point, it is imperative that businesses take the necessary steps to scale successfully.

Define the value of your business

There are countless ways to use AI.  How do organizations decide what to focus on?  To scale successfully, start by defining what value means to your business.  Then, evaluate and prioritize various AI applications against those strategic goals.

Rework your workforce

A diverse and restructured workforce is needed to keep up with and scale the increasing pace of AI.  Despite initial fears that artificial intelligence and automation will lead to job losses, the future of AI depends on human-machine collaboration and the need to reshape talent and ways of working.

Establish governance and ethics frameworks

Organizations should design their AI strategy with trust in mind.  This means building the right governance structures and ensuring that ethical principles translate into the development of algorithms and software.

Successful application of these factors can help organizations unlock exponential value and remain competitive.  AI is no longer just a “nice to have”, but essential to the company's future.

AI Ethics

No introduction to artificial intelligence can be complete without addressing the ethics of AI.  AI is advancing at breakneck speed, and like any powerful technology, organizations need to build trust with the public and be accountable to their customers and employees.

At Accenture, we define "responsible AI" as the way we design, build, and implement AI in a way that empowers employees and businesses, and impacts clients and society alike.

believe it

All companies using AI are subject to intense scrutiny.  Ethical theater, when companies engage in unpublicized gray area activities that promote the responsible use of AI through public relations, is a recurring theme. 

Unconscious bias is another.  Responsible AI is an emerging capability aimed at building trust between organizations and their employees and customers.

Data security

Data privacy and unauthorized use of AI can harm both reputation and system.  Companies should build privacy, transparency and security into their AI programs from the start, and collect, use, manage and store data securely and responsibly.

Transparency and explanation

Whether creating an ethics committee or revising their code of ethics, companies must establish a governance framework to guide their investments and avoid ethical, legal and regulatory risks. 

 As AI technologies become increasingly responsible for decision making, companies need to be able to see how AI systems reach a given outcome, taking those decisions out of the "black box."  A clear governance framework and ethics committee can help develop practices and protocols that ensure your code of ethics translates well to the development of AI solutions.

control.

Machines don't have minds of their own, but they do make mistakes.  Organizations must have risk frameworks and contingency plans in place in case something goes wrong.  Be clear about who is responsible for the decisions AI systems make, and define a management approach to help escalate issues if necessary.