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Artificial intelligence (AI) is continuing its migration out of the research lab and into the world of business. Leading companies across hundreds of industries are harnessing its power — from banks analyzing countless data points in seconds to detect fraud, to call centers deploying chatbots to improve customer interactions.

These early uses are still fairly limited, but huge advances in deep learning (a subset of machine learning) are starting to impact AI in ways that will soon help society and business tackle a wider set of more general problems. Such advances will also make it possible to automate more complex physical tasks that require adaptability and agility.

At Salesforce, we believe AI has tremendous potential for improving the way organizations operate (and you can learn how AI is built into our entire Salesforce Customer 360 here). This next wave of AI will enable companies to continuously adapt processes based on past experience — ushering in vast improvements in customer targeting, for instance, because deep learning algorithms will be able to spot patterns in behavior that are more likely to lead to sales. In supply chains and manufacturing, potential benefits will include predictive maintenance of equipment, along with yield and inventory optimization.

 

Dr. Richard Socher, Salesforce's Chief Scientist, and his team of researchers introduced exciting new
AI breakthroughs at Dreamforce that promise to fundamentally change the way we work.

 

This future AI has the potential to revolutionize how companies engage with customers, compete with each other, and grow within the market.

While these advances may not fully mature for the next five to 15 years, they are certainly on their way. So with the future of AI set to change the rules of business, here’s what companies need to know about readying themselves for its impact on their industry and workforce, to better reap its benefits.

 

AI statistics: measuring the impact

Research shows a growing eagerness to capitalize on the opportunities AI presents. 

  • With leading companies using the technology to help them make better business decisions through data and through better predictions of customer behavior, a majority of customers (51%) say their expectations of companies are now being influenced by AI. [“State of the Connected Customer,” Salesforce Research]

  • At the same time, AI-powered developments like individualized recommendations and automatic order fulfillments are raising the bar against which customers judge companies: 48% of consumers and 63% of business buyers now expect personalized offers. [“The AI Revolution,” Salesforce Research]

  • Top sales teams, in particular, are realizing the power of using AI to craft compelling customer experiences, focusing specifically on automatically recommending products to customers based on their preferences. The technology has become the top growth area for sales teams, and its adoption is forecast to grow 155% over the next two years.

 

How are companies using AI?

As these statistics show, many companies already recognize the benefits of AI-based systems. AI is fueling powerful ways to help companies get closer to their customers, and share information and knowledge in a personalized exchange. 

Recent consumer research shows that many customers also appreciate a number of everyday technologies that would be impossible without AI — whether or not they recognize these things as being AI-driven. For example, credit card fraud detection, email spam filters, automatic reminders, and predictive traffic alerts are among the most popular AI use cases. At the same time, more than half of customers are fond of AI-powered voice-activated personal assistants. Millennial and Gen Z customers are nearly twice as likely as traditionalists and baby boomers to connect with companies via voice.

 

 

As more companies start to adapt deep learning-powered applications (speech recognition interfaces, for example) for their businesses, such AI benefits will become even more pronounced. “The rise of digital voice assistants — such as Amazon Alexa, Apple’s Siri, and Google Assistant — are leading a fundamental change that will impact every business,” said Peter Schwartz, Senior Vice President, Strategic Planning, at Salesforce. “Customers, partners, employees — every individual — will expect to engage with brands across every industry through voice-enabled interfaces.”

By continually analyzing vast troves of data in real time, the next wave of AI-powered assistants will rapidly grasp customers’ priorities and predict their needs. Brands that want to communicate with customers as quickly as possible anywhere in their daily lives will be able to take advantage of AI-powered platforms to deliver timely, hyper-personalized experiences.

The future of AI will also give companies the capabilities to analyze sentiment — for example, what customers think based on their social media posts. “Sentiment analysis searches language to pinpoint the opinions of your customers on, say, Twitter, and estimates the emotional reactions shown toward a product,” said Richard Socher, Chief Scientist at Salesforce. “This could allow you to see if a marketing campaign was working in real time.”

 

How will the future of AI affect jobs?

Sixty-two percent of hiring managers say that AI will change how we work within five years. However, this approach isn’t about replacing people’s jobs with robots. “Our research found that machine learning seldom, if ever, replaces entire occupations. Instead, it replaces or transforms specific tasks within an occupation,” said Erik Brynjolfsson, Director of the Massachusetts Institute of Technology (MIT) Initiative on the Digital Economy.

Experts predict that the future of AI will be characterized by broader levels of employment, because it’s technically difficult to automate unpredictable and complex physical tasks. And while machines may take over tasks involving high-volume, routine work, they don’t perform so well when it comes to abstract tasks involving human capabilities like empathy, judgment, creativity, inspiration, and leadership. Innovating and managing people — to take just two examples — will be almost impossible to hand over to a robot, no matter how well programmed.

“There are some things about running an organization that I don’t think are going to change, even in the face of these crazy, powerful technologies: articulating a compelling vision that will attract talent, customers, and stakeholders; being true to that vision; and managing the culture that you’ve created to go tackle those visions,” said Andrew McAfee, principal research scientist at MIT and co-founder of the MIT Initiative on the Digital Economy. “Those are deeply human skills, and leaders who are good at them are going to become even more valuable.”

AI expert Dr. Kai-Fu Lee agrees.“Humans can’t just be substituted by machines or data,” he said. “I believe that creativity is something that cannot be replaced. Storytelling in fields such as public relations is an area that I think will flourish. Empathy is also important, particularly in human resources departments as employees deal with the angst brought about by change.”

Accenture forecasts that AI could boost U.S. labor productivity by 35% by 2035. These gains will come from computers doing what they have always been good at: allowing us to make better use of our time.


How should companies prepare for AI?

To ensure employees and AI-powered machines can work together effectively in an AI-driven future, companies will need to profoundly re-evaluate their workforce development strategies.

On a broad level, people will need help adjusting to more fluid and adaptive business processes. This means getting ready for organic teams comprising both humans and advanced AI systems. 

A critical aspect here is to encourage an open mindset among employees, to ensure they trust rather than fear applying automation to various routine tasks. “Trust is needed across the board — in the technology, in business leaders, and in the training for business users — to ensure the path to an AI-enabled workforce is smooth, and we all benefit,” said Marco Casalaina, Vice President of Product Management at Salesforce Einstein.

Encouraging employees to experiment and create tests to produce effective business processes is vital. Executives should also commit to using responsible AI that is transparent, accountable, and unbiased.

 

How will AI impact training and upskilling?

The transformative nature of AI will also require companies to rethink their approach to training. To avoid a persistent shortage of skilled labor, businesses must develop strategies to help employees upgrade their proficiencies and quickly gain the new skills they need to exploit the power of AI.

“Business has a responsibility for upskilling workforces for the AI age — a role that cannot fall only on governments,” Jim Wilson, Managing Director of Information Technology and Business Research at Accenture Research, told Salesforce in a recent interview.

Research shows that two-thirds of U.S. hiring managers believe that implementing workforce development programs will help them prepare for future disruptions or innovations. Despite this, many businesses have been slow to act. They’re held back by budgetary constraints, lack of time for employees to participate in training, and lack of appropriate training technology.

“If we are to adapt to AI, it starts with prioritizing workforce training programs. It’s crucial that we’re as invested in building individuals’ capabilities as we are in building technological capabilities,” said Vala Afshar, Chief Digital Evangelist at Salesforce. “Not addressing workforce development and reskilling will only widen the digital skills gap, threatening businesses’ ability to compete in the Fourth Industrial Revolution.”

 

 

Workers will need continual retraining if they are to keep up with the evolving job requirements of the new wave of AI. A shift to lifelong learning is essential. And if technology is changing every few months, skills development programs will need to follow suit. Using immersive new technologies like virtual reality can accelerate the speed and scale of training, and allow companies to attract new talent.

“Businesses also need to think about how they provide training,” said Miguel Milano, President of Salesforce in Europe, the Middle East, and Africa (EMEA). “Apprenticeships offering practical on-the-job training, in-house training programs for non-college-educated entry-level employees, and partnerships with external workforce development agencies all play an important role.”

 

What are the disadvantages of AI?

AI provides amazing opportunities to meet the most specialized customer needs and create entirely new business models. It has the ability to address some of the most pressing societal challenges. But as AI-based decisions start to have a greater impact on human lives, ethical questions arise about how the technology is affecting society. How can we ensure AI treats everyone fairly, and to what extent are organization responsible for protecting privacy?

Ideally, when an AI system recommends a course of action — for example, regarding a patient’s medical treatment or a bank customer’s home loan application — the same recommendation should apply to everyone in an identical situation. Computers, in theory, are not subject to the biases that influence human decision-making.

Yet AI systems are designed by humans and are only as good as the data fed into them. Even when one algorithm makes another, the original algorithm was made by humans and is therefore subject to human bias. An insight or prediction isn’t more honest simply because a bot generated it.

“For all their enormous potential, current success [with deep learning models] is based on fitting to patterns of historical training data,” said Timnit Gebru, research scientists on the Ethical AI team at Google AI. “There’s still much work to do to train models how to reason. They can only be trained to find patterns in historical data. The problem is that this training data isn’t neutral  — it can easily reflect the biases of the people that put it together. That means it can encode trends and patterns that reflect and perpetuate prejudice and harmful stereotypes.”

 

How do we ensure an ethical AI?

The process of managing the threats of biased AI starts with humans proactively identifying and managing any such bias — which includes training AI systems to identify it.

“Core to this is making sure that the people who are building AI systems reflect a diverse set of perspectives,” said Richard Socher. “A homogenous group may only hear opinions that match their own — they’re limited to what they know, in other words, and are less likely to spot where bias might be present.” 

With such guidance, organizations can curate bias out of their training data to mitigate its negative effects. This can also help to make AI systems more transparent and less inscrutable, which in turn makes it easier for companies to check for any errors that might be taking place.

At the same time, as with any technology, trust in AI systems depends on whether the systems themselves can operate reliably, safely, and consistently. So it is also vital that these systems have appropriate privacy and security protections. Simply put, people will not share personal data — the essential information that guides AI — unless they are confident their privacy is protected and their data is secure. 

“CEOs must become ethical stewards of customer data,” said Zvika Krieger, co-leader of the World Economic Forum’s Center for the Fourth Industrial Revolution. “Not only because it’s the right thing to do, but because if they don’t, then it’s only a matter of time before customers grow resentful, and reject those companies that are not good stewards of [their] information.”

AI is possibly the most advanced tool ever developed, but just like a hammer, it can be used for good or bad. If we can properly address the issues of how to use AI responsibly, transparently, and fairly, it is much more likely to be a useful tool in the tasks of building business growth and creating a better world.


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