18 Jul Artificial Intelligence and Your Business
If there has been a single constant in the world of business for the last 4-5 years, it has been the concept of artificial intelligence (AI). In fact, there is a widely held “fear of missing out” (or FOMO) for artificial intelligence, of missing the bandwagon and of being left behind by more agile AI-powered competitors. As a result, organizations of every size—and in every industry—have heard the clarion call to add artificial intelligence to their operations, without necessarily knowing how AI can add value to the products and services that they provide to customers, if their operating data is actually AI-friendly, or how to actually implement AI capabilities with their products and services. (Note: AI is one of the components of the vision of Industry 4.0. Read Nubik’s ebook on how businesses can meet the challenges of Industry 4.0.)
There has been a corresponding explosion in the number of companies working on AI technology for business in a dedicated fashion—Montreal’s Element AI is one example—as well as large cloud IT platform providers adding AI to their offerings. Google Cloud, Amazon Web Services, and Microsoft Azure each offer dedicated artificial intelligence solutions—typically based on machine learning and big data—to organizations in a subscription format designed to supplement an organization’s existing IT infrastructure. Bank of America estimated the market for AI solutions to be worth US$153 billion by 2020. (Salesforce eBook)
What do we mean by artificial intelligence?
Wikipedia defines artificial intelligence (A.I.) as “intelligence exhibited by machines. … Colloquially, the term ‘artificial intelligence’ is applied when a machine mimics ‘cognitive’ functions that humans associate with other human minds, such as ‘learning’ and ‘problem solving’”.
In practice, artificial intelligence is a bit of a catch-all term referring to a number of technologies that automate or augment business processes or deduce information from business data. In a business context, these include machine learning (covering capabilities such as pattern matching and rule building), computer vision, sensing, emergent behaviours, and robotics. We’ll talk more about the first two technologies in a business context.
How can AI enhance business?
Artificial intelligence can enhance business in a number of ways. For many organizations, irrespective of industry, artificial intelligence can be used to derive new insight and meaning from the production, sales, and support data that are generated every day during normal business operations. Drawing upon ever greater “data lakes” and other sources of big data, artificial intelligence can be used to augment decision support systems or expert systems beyond the capabilities of traditional point solutions. Machine learning capabilities, enhanced by cloud-based AI platforms that leverage the power of graphics processor units (GPUs) from Nvidia and AMD—the same processors that power real-time, high resolution 3D video games—make it possible to infer new patterns, discover new behaviours across disparate data sources, and generate other insights that enhance the product development lifecycle, eliminate manufacturing errors on the production line, reduce the sales cycle, and optimize the customer lifecycle.
In the case of manufacturers and high-tech organizations, one branch of artificial intelligence in particular has opened up a world of possibilities. Computer vision, that leverages video with object recognition capabilities powered by machine learning that is often based in the cloud, can be used to identify defective parts on the production line or position manufacturing equipment more precisely, enabling organizations that deploy these technologies to achieve “smart manufacturing” status and the productivity gains that come with it.
Taking advantage of artificial intelligence is another matter
To properly take advantage of the promise of artificial intelligence, specifically machine learning, organizational data needs to be available in a format that allows it to be ingested, learned from, and acted upon. Without data in such a format, the promise of artificial intelligence remains just that, a promise.
Many organizations have taken the leap to become AI-enabled by adopting third-party, off-the-shelf AI software, or have contracted to develop custom AI solutions, only to find that their data was not appropriate for analysis and learning or, if it was optimized, had no idea how to take advantage of the insight provided to deliver value. Before taking that leap, it’s important to have a clear understanding of the production, sales, and support data that is available across the organization, as well as the types of insights that one hopes to derive from the data. Done the wrong way, the adoption of AI is little better than “garbage in, garbage out”.
The good news is that if you use solutions based on the Salesforce platform, not only is your data already in a format that allows it to be leveraged by artificial intelligence, but you get an artificial intelligence engine essentially “for free”. Known as Salesforce Einstein, this artificial intelligence engine has been woven into the most important Salesforce solutions, including the Sales, Marketing, Community, Analytics, Platform and Commerce platforms. Salesforce Einstein was released in the fall of 2016 and so has therefore had the chance to propagate widely over the last 7-8 editions of Salesforce, with each new release of Salesforce bringing extended Einstein support and capabilities.
What does Einstein provide?
Salesforce Einstein works behind the scenes, leveraging all of the lead and customer data that you have stored in Salesforce, to provide actionable insight and recommendations with no intervention necessary on the part of the Salesforce user.
In a Sales context, Einstein offers predictive lead scoring and new insights based on analysis of the purchasing history and behaviour of existing customers, as well as support for upselling by recommending complementary products and services. In a Marketing context, Einstein identifies the appropriate content pieces, the target audience, the optimal channel, and the best time to interact with prospective or existing customers to drive enhanced engagement.
Salesforce Einstein’s powerful intelligence and analytical capabilities can also be tapped by custom applications that are built on the Salesforce platform. Additional capabilities such as prediction modelling, online bots, computer vision, and language analysis can also be added to any application.
After surveying the different sources of data in the organization and identifying the types of useful insights that you hope to achieve with your data, the next step is to identify the technology platform to get there.
If you are looking to enhance your business operations with the power of artificial intelligence, a cloud-based Salesforce solution for customer relationship management, marketing, field service, or support can provide you with what you need to hit the ground running, bundling leading CRM, marketing automation, and support capabilities with a powerful AI engine. If you are already a user of Salesforce and want to know more about how to leverage the capabilities of Einstein with your existing business data, you should contact us.
By Stéphane Poirier, Marketing Director
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