After all, a few years ago the notion of a small business using such technology — which was arguably even less well-understood than it is now — would have seemed unusual. Possibly even unrealistic for a small business to use.

AI is often depicted as extremely complex, sometimes powering the kind of robotic creations that are staples of science fiction movies. From a business standpoint, it also looks expensive and custom-made, which would likely make it out of reach for small or medium-sized companies.

While some of the early adoption of AI certainly occurred within large enterprises, the maturation of the technology has reached a point where it is not only accessible to small businesses, but increasingly becoming integral to long-term growth.

AI defined

It’s important to recognize that “AI” can be a broad term, and often encompasses a number of different technologies. A good example is natural language processing — the kind of AI that allows voice recognition software to understand what you say when you ask something of your smartphone’s virtual assistant.

Machine learning, on the other hand, involves the use of algorithms to analyze data within business applications to detect patterns or trends that indicate what might happen in the future. It’s this predictive capability that tends to be game-changing for businesses of all sizes.

The longer you run a business, for instance, the more likely you’ll want to get ahead of the unexpected. This could include surges in customer demand that seem to come out of nowhere, or a spike in customer service calls based on an issue with one of your key products. Small businesses in particular are often crunched for time and resources, so having some advance warning can help ensure you respond to whatever comes their way with agility and effectiveness.

Still . . . it also takes time to learn about AI, you might argue. You may worry your business is somehow not ready yet. You might have budgetary concerns.

Those are all valid points, but they’re not enough to just ignore how these technologies are changing the way companies run. Here are more reasons you should care about AI:

1. You might already have AI

Unlike other waves of technology, AI doesn’t necessarily represent some new shiny product you have to go out and purchase.

Many vendors have either already woven AI technologies into their existing business applications, or are in the process of doing so.

Rather than some kind of robot that works at a desk, AI often augments or adds features to other products and services. This includes Salesforce, where we’ve used Einstein to bring value across our entire line of CRM, marketing automation and customer service tools.

Make sure you’re aware of any AI capabilities your existing applications might have introduced, or that may be on the product roadmap for later on. There’s no point in failing to take advantage of AI if you can do so right away.

2. Your customers may start to expect you to use AI

AI is quickly becoming pervasive in a range of applications, from those used by major banks to retailers and other industries.

Machine learning is often what powers the product recommendations a customer sees when they’re browsing an e-commerce site, for instance. In other cases, AI is helping companies personalize the way they market products and services down to an individual customer level.

Imagine the disconnect, then, if your business not only can’t demonstrate that kind of knowledge about your customer, but instead forces them to answer questions you might already have asked before? It’s far from an ideal customer experience.

Customers might not fully recognize or understand that AI is the force behind a company’s personalization efforts, but that doesn’t mean they aren’t coming to expect it from their favourite brands.

There’s also the expectation of being there when customers need you. Just look at chatbots, which are becoming commonplace on websites as a way to get information and questions answered. AI not only allows chatbots to resolve the most common customer inquiries, but to do so on a 24/7 basis. If one vendor offered that kind of support and another didn’t, which one would you give your business to?

3. You can’t afford not to try AI

Chances are at least one of your competitors is already using AI, which means customers might compare the experience they have between your firm and theirs.

Even if that’s not the case right now, AI can be an incredible time-saver by bringing together massive amounts of data and making sense of it faster and better than any human will be able to do.

More importantly, AI tends to be less prone to error than human beings who get tired, distracted or both. No one can afford mistakes, particularly if it costs them a customer or lands them into legal hot water. In that sense, the business case for AI becomes hard to ignore when it means you can boost productivity while also reducing risk.

The usefulness of AI doesn’t end there, however. AI is, in many ways, the next step in the move the most successful business owners have already made towards data-driven decision-making.

While you might still trust your gut instinct on some issues, early analytics software allowed many entrepreneurs to better understand what was really going on in their company before they made a particular move.

AI does something similar, but isn’t restricted to looking only at what happened in the past. That means you can use the technology for a higher order of decision-making. This isn’t limited to the overall direction for your business, either, but the way you coach, manage and lead your entire team.

Next steps

Instead of just thinking, “I need to learn about AI,” reframe your intention. Think of your biggest business goals or priorities. Ask yourself, “How could AI help with something like that?”

Talk to your vendor partners, members of your team or even your best customers about what they’ve seen or learned. You’ll likely find there’s an AI technology that could be applied.

From here on in, you won’t have to wonder why you should care about AI. You’ll only wonder why you didn’t care even earlier.

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Businesses now face a shared challenge: how do you predict the unpredictable?

Here’s what you need to know to make sure your AI predictions support your customers in this time of uncertainty.

Where AI predictions can go wrong

Think about how many changes you’ve made in your life over the last several weeks. Multiply that by thousands, millions, and even billions of other people making similar lifestyle changes, and you can imagine the uncertainty it creates for businesses that rely on AI in their customer workflows.

Previously reliable models are suddenly unable to accurately predict an outcome:

• A forecasting model can’t cope with an unforeseen need for increased staffing.

• A lead scoring model for sales has no knowledge of how widespread school closures impact customer meetings.

• Churn models don’t include variables for social distancing or sudden massive job loss.

AI uses historical data to create accurate predictions. But this pandemic is throwing off predicted outcomes. While models can adapt and learn, the rapid changes currently in motion make it difficult for them to learn fast enough.

What can you do in the midst of this volatility? Use these tips to help focus your efforts so you can best support customers today and tomorrow.

6 tips for using AI to empathize with your customer

Now is the time to take a closer look at your AI strategy to ensure accurate data and predictions support a positive customer experience. Companies that get the customer experience right lay the foundation for long-term loyalty. Here’s how.

1. Examine your data and dashboards

Take a close look at dashboards that track important business KPIs: how have they changed? Are your customers waiting longer than usual for resolution?

Slice your data by hour, by day, by week — even by records related to COVID-19. This will help you isolate normal (generally seasonal) patterns from the current shifts in customer behavior.

But take note: if something looks different from one day to the next or one week to the next, it might just be a red herring! Ask yourself why you’re observing specific new behaviors: is it a one-off or is it the new normal? For example, customers buying excess toilet paper isn’t necessarily a new trend, but prolonged purchases of immune-boosting vitamins may be.

2. Inspect your AI models

A powerful, data-driven way to understand how your business is impacted by the pandemic is to compare AI models built on different segments of data.

Use data from last year to build a model, and compare the model to data from this year, or this month if you have enough. Are the models changing? Which attributes were most important? Do they tell you something about how the data is shifting?

3. Monitor, monitor, monitor

It is crucial to know what happens with predictions over time. For example, if you predict how many customers will convert to paid after a free trial, will they exhibit the same behavior given the current situation? Build reports to compare your predicted to your actual values and slice by time again. Has this changed over the last few weeks? These comparisons will help determine which changes are due to COVID-19 factors and will guide you in providing the best support to your customers.

4. Don’t (over)react to every new insight

Pay attention to all areas of the business where you leverage AI. Your fraud detection algorithms looking for anomalous behaviors may go haywire because everything is in a state of flux. These anomalies may be the new normal or may return to the way things were before.

The challenge is we simply don’t know yet, so you need to wait and see.

Depending on where we land, this will determine how to respond in the new steady state. Do you keep this data from future model training? Do you leverage it differently? You will need to continue to monitor your predictions and continue to adapt.

5. Update your business processes

A prediction is no better than the business process it powers. After all, you may be able to perfectly predict the future, but if it doesn’t drive a business outcome, it’s not very useful.

During this time of rapid change, you may need to make adjustments to your automated workflows. Maybe you have a model that predicts if a customer will pay an invoice late which kicks off a reminder email if the likelihood is high. Be sure to adjust your customer communications so the message to customers is empathetic and compassionate. The last thing you want to do is send a nasty-gram that creates more stress and alienates the customer.

6. Above all else, win as a team and lead with empathy

It takes a village to solve this problem.

Bring together your business experts and your Salesforce admins to examine models. Bring in analysts to slice your data and discuss insights with them. Everyone from your product teams to sales teams can bring diverse perspectives and collaborate on the right way forward.

In our day-to-day lives, we are excited about the possibilities of AI, and the opportunities it brings to our business. It can be easy to forget that every data point is a person. But in this crisis, more than ever, we need to remember this simple fact — every one of us is living this shared experience. How do you want your company’s response to be remembered?

For more business and leadership inspiration, check out our entire Leading Through Change series.

The Einstein team is here to help you through this uncertain time. If you and your team need help to audit your predictions and create an action plan to move forward, please reach out to your AE to get in touch with one of our Einstein experts. Read more about how to get started with Einstein Artificial Intelligence on the Einstein Hub.

The post How to Adjust Your AI Strategy to Address Volatility in a Time of Crisis appeared first on Salesforce.

In particular, there was a strong focus on artificial intelligence (AI) and technology in the day’s programming. Here’s what we found out today:

1. Trailblazers are more impactful together

We kicked off the day by celebrating Trailblazers creating change for their customers, companies, and communities. These are the leaders and change-makers using Salesforce Customer 360 to transform their company. “That is why we’re here as Trailblazers: to improve the state of the world with trust, customer success, innovation, and equality,” said Chairman and Co-CEO Marc Benioff. As Marc, Co-CEO Keith Block, and fellow Salesforce executives took the stage throughout the morning, the online audience and attendees got a preview of how we can build a connected and smarter Customer 360 together and how we can enable a single source of truth.

Read our opening keynote highlights post for more details.

2. Diversity and soft skills are important in the future workplace

As more organizations move towards digital transformation, they’re realizing the key role that AI plays in this process. It’s the driving force behind changing business models, consumer expectations, and our workforce. Chief Technology Community Officer at the Kapor Center Lili Gangas and Co-Founder and CEO of pymetrics Dr. Frida Polli discussed the potential and pitfalls of AI, the reskilling problem our workforce faces, and the need for more diversity to recognize and prevent bias in AI. Diving into the conversation, Dr. Polli jokingly remarked, “AI is like teenage sex: everyone says they’re doing it, but no one actually knows what it is.” She went on to initiate a discussion on the mind of workers everywhere: AI and jobs. Dr. Polli believes that with growing AI, we need to look more at people for their soft skills and their potential. “Once we find the right balance between historical jobs and new industries — and train people — that’s the way to go.”

The discussion also touched on the importance and need for more diversity in the AI field. “When we have a homogenous group creating technology, if you’re not thinking of the unintended consequences, you’re doing it wrong,” Dr. Polli said addressing the tech industry’s lack of representation. “We’re leaving a lot of undeveloped talent on the table and that’s not good for anybody.” Gangas agreed and brought up the need for underrepresented communities to ask tougher questions of their industries. “To create new systems, we need new founders,” she said. “If someone isn’t asking tough questions, you’re building blindly. I think we can do better and we should.”

3. The potential of 5G is like magic

The excitement surrounding the possibilities and potential of 5G technologies grows every day, but there are equally plenty of questions about how 5G can be rolled out responsibly. Dreamforce welcomed Director General of the GSMA Mats Granryd, Chairman and CEO of KT Corporation Hwang Chang-Gyu, Tech Ambassador of the Danish Ministry of Foreign Affairs Casper Klynge, and moderator Fortune’s Sr. Editor Ellen McGirt to discuss the cascading impact of 5G and how businesses can prepare.

Though 5G may seem like magic, Ellen asks if it is “good magic.” To answer this question, the panel discussed the realistic roll-out of 5G networks, the positive impact of 5G connectivity in remote villages, and the power of lower latency and higher “speed lanes.” As the panel wound down, Klynge, the diplomat, asked the audience to consider new ways of cooperating and new alliances we will need to ensure inclusion of data-security, inclusivity, equality, and sustainability in embracing this new technology on the horizon.

4. Preventing bias in AI is still a challenge for many

The conversations around ethics and responsibility in the use of data, technology, and AI solutions continues to grow. However, there’s still uncertainty in what actionable steps businesses can take to manage bias in AI and ensure organizations are paving the way for digital transformation in an ethical way.

In a fascinating panel, World Economic Forum’s Head of AI and Machine Learning Kay Firth-Butterfield, Co-Founder & Executive Chair of Socos Labs Vivienne Ming, and Salesforce’s Architect of Ethical AI Practice Kathy Baxter discussed the state of ethics in AI and shared their insights on what steps all companies can take.

For starters, It’s all about practice. Ethics and AI starts with asking the right questions like, “What needs to be solved” or “Is this something people want or is it something they need?” “Ethics is a lived experience and making hard decisions when your interests and society’s needs diverge,” Ming advised. Firth-Butterfield agreed with this assessment. “We need to be thinking about the entire process as we design, build, and sell.” This is important because ethics isn’t something that can be learned in a classroom – it’s something that needs to be put into practice.

Similarly, another important benchmark for creating ethical AI is asking yourself if what you build makes people better — is humanity better for it. “Always ask yourself: does this make me a better person, even when I turn it off?” Ming says. Firth-Butterfield explained that we should not think of AI as surpassing our abilities, but about AI helping us overcome what we’re not so good at. “We really need to think about if we really need AI everywhere, and making sure that AI is lifting us up as humans, rather than oppressing us.”

Whew, that’s a wrap for day one! Get a good night’s sleep and stay hydrated because we’re going to crank up the energy again tomorrow for another day of learning and inspiration.

Bonus Insight: Apple CEO Tim Cook believes values enhance innovation

In the same theater where many of Apple’s most revolutionary products have been unveiled, Apple CEO Tim Cook joined Marc Benioff to discuss mobile’s role in the enterprise and the intersection of innovation and values, such as equality, sustainability and privacy.

Befitting yesterday’s announcement of two new Salesforce apps on iOS and an enhanced Mobile SDK, they discussed the importance of app development for business. “For too many still, mobile is about browsing, email, and messaging,” Cook said. “But arguably, the way you change the business is using mobile apps.” He gave two examples of this, including how Hästens mattress company built a custom iOS app to reduce mattress sale configuration time by 90%.

The conversation pivoted to values and how Cook leads Apple to continue 40 years of innovation while maintaining its focus on values, like sustainability and equality. He openly shared how he came to his personal sense of purpose in his late 30s: “At some point you recognize the reason we are all here is to help someone else. That is the sole reason. And once you get that in your head, life gets so much simpler.”

The post What We Learned on Day 1 of Dreamforce ‘19 appeared first on Salesforce.

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.

The post How the Future of AI Will Impact Business appeared first on Salesforce.

The changing customer

Businesses are already realizing that customers, both business and consumer, are becoming more difficult to attract, influence, and retain. Why is that?

• The purchasing journey is becoming complex, and sales teams are responding by gaining a deeper understanding of the customer journey. Constantly connected to colleagues and cohorts, today’s buyers validate views, invite opinions, and share thoughts. Bombarded by marketing information, they are filtering out noise, and focusing only on relevance and sales organizations that truly understand their pain points.
• The purchasing journey is now fully multi-channel, as buyers explore and compare online, on mobile, in stores, at home and work. Smart companies work to engage them earlier, create seamless experiences and build enduring, trusted relationships.
• Personalized experiences are creating better customer connections. Customers respond to one-to-one experiences that go beyond product customization and spans their entire customer journey. Bespoke manufacturing is common at an industrial level, but personalization must go further. Customization via product options has long been a part of luxury car marketing, but Jaguar Land Rover has put personalization at the heart of sales at its Westfield store. It embraced the multi-channel purchasing journey, enabling the purchasing process to be continued and concluded online.
• Customers increasingly seek outcomes and experiences rather than products and features. They want a brighter office, not lightbulbs, and a cozy bedroom instead of a heater. Consumers are welcoming brands that exceed their expectations and immerse them in delightful experiences.

The implications may seem more relevant to retailers – but they aren’t. Understanding customer motivations and values can inform every aspect of sales and marketing, inform product development and spark manufacturing innovation. And with the growth of direct-to-consumer as a business model, these changing customer demands are becoming absolutely fundamental to achieving success.

If customers are so central, where do you start?

To adapt to an increasingly connected, customer-centric world, manufacturers must recognize:

1. Customer visibility and understanding have become critical

Customers are always seeking a a way to solve their own problems – so to develop and sell well means understanding those needs. To enable value for someone, you must know what value means to them, understand their motivations, and how they identify their needs. Unfortunately, some manufacturers have no direct customer relationships, particularly if their customers buy via channels like dealers and distributors. Even those that sell directly often keep customer data siloed from other business areas – whether because they don’t have the right technology in place or because it hasn’t historically been part of the company culture to share this information. IT systems usually become complex over time with data spread across different databases as well as production and warehousing systems never designed to interact with back office software. It is tough to see customers clearly, make that knowledge accessible to business users throughout the business, or build on it to drive better engagement. Uniting your customer data, whether internally or in collaboration with partners, must be a business priority for manufacturers who want to sell more directly, or engage more directly, with their customers. It requires flexible systems of intelligent engagement to complement your systems of record and functional IT, that enable you to engage customers in the right way, on the right channels, at exactly the right times to gain their attention.

2. Connected customers need great experiences

Improving the overall customer experience can be seen as the retailer’s domain – but the benefits that will explode from IoT-connected products will form a fundamental part of the customer’s experience. Putting customer experience and service at the forefront of your thinking should become the manufacturer’s responsibility too – even if service is devolved to others. “A consistent focus on customer service is a crucial ingredient for sustainable performance, especially in challenging times” insists the Institute of Customer Service. So, when a customer has a problem, even if a partner manages support for that customer, you need to be fully confident in the quality of service. Each customer experience influences not only their future decisions but those of others, as customers now share experiences freely – especially bad ones. Creating seamless, valuable, enjoyable experiences and service excellence for customers, whether they deal with you or partners, is a vital ingredient of success in a competitive world. It means creating transparent platforms which allow you and partners to deliver experiences collaboratively.

Securing your future

Manufacturers can secure their future by delivering products that customers want and consistently delighting them across all customer touch points – from the sales process, to customer service, to upsell and cross-sell – all with the goal of delighting that customer so that, when the time is right, they are excited to do business with you again. The future rests on redefining the goal of manufacturing around customer success, not product sales – something Forbes cited as a top ten customer service trend for 2017. Connected products, supported by predictive customer service that anticipates customer needs, will require the right systems in place that can simplify mountains of complex, siloed data. Having a single view of the customer that is available to all employees will enhance those employees’ ability to deliver great customer experiences, as well as enable you to plan differently and innovate around customer needs. Having this complete customer view requires implementing seamless ways to manage customer interaction and engagement, as well as having access to the tools to analyze business and customer data to drive smarter decisions. The manufacturing sector is in the midst of a rapid change. For some this will present the opportunity to innovate and create new value – but, for those who fail to adapt or recognize the fundamental changes, it will present significant risks. Taking a whole-company approach to create customer centricity means connecting employees to each other, as well as to customers, linking back and front offices, and eliminating data silos. It means embracing your complex partner ecosystem and providing them with platforms that enable collaboration around the customer so that they too can deliver amazing customer service and experiences. Adapting for the future of manufacturing is about creating agility and insight to drive success for everyone – and Salesforce has been enabling customer success since its inception. We have already helped thousands of companies connect to their own customers in a whole new way and drive more customer success. A great place for manufacturers to begin their transformation is with their sales organisation. Download our e-book to read more about how Salesforce solutions can help manufacturing companies to success in the Age of the Customer and deliver personalized customer engagement at scale.

This post was originally published on the Salesforce U.K. Blog.

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