If you send messages on your mobile phone and have the “predictive text” feature turned on, you’re familiar with AI. If you’ve clicked through recommended purchases on Amazon, or started watching a movie or TV show on Netflix that was “Suggested for You”, you’re familiar with AI. If a real-time virtual agent pops up on a website to help you with a question or purchase decision, you’re familiar with AI. Does your Gmail account remind you of unanswered emails, or of ones you still need to respond to? Maybe you’ve even been in a Tesla? Then yes indeed, you’ve experienced AI…
“Hey Siri, what is Artificial Intelligence?”
Siri: “Okay, check it out… Artificial intelligence [involves] any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals.”
That’s an edited definition of Artificial Intelligence – or “AI” – from asking the question to Apple’s Siri virtual assistant. Some human agency was [involved] to edit it down as needed, and despite the role of machine learning in AI, there’s always going to be some required. Yet beyond editing choices, human agency – or even platform lock-in – could’ve equally sent the same question to Amazon’s Alexa, which is now a more ubiquitously pleasant sounding virtual assistant than Apple’s Siri. If we’re counting, it could also be directed to Google’s non-personalized “Google Assistant”.
Whichever the platform, there are several virtual assistants pushing into the centre lanes of technology roadmaps worldwide. They can integrate into “smarthome” technologies such as Next (also by Amazon) to improve life off-the-clock, or integrated into the workplace for boosting revenues or efficiency gains, as with business-centric office assistants such as Microsoft’s “Cortana”. Yes, we’re well past the days of Microsoft’s “Clippy”!
“Just as Amazon now uses data to tee up the products you’ll buy next, AI will learn to focus on the characteristics that companies and managers want from workers.” [1]
Alexa is a centrepiece of Amazon’s strategies, but it isn’t there simply to sell more products online. Rather, Alexa can transform sales from a direct pitch to the customer into an ongoing process of customer learning and discovery, i.e. as a customer/user experience. This process ultimately reveals consumer needs – ironically – in what seems like a more natural and human way, and then can assist with Amazon’s ecommerce and delivery functions.
Similar functions can exist for business use cases for AI that might include:
- résumé and CV pre-screening in deeper ways than just keyword matches;
- dynamic and predictive business travel estimations based around contextual time factors for pricing and reimbursements;
- contract review that can contextually weigh and decide upon completion, with potential to be automated securely in the background (e.g. through verifiable blockchain transactions);
Artificial Intelligence is therefore not an end product for companies to purchase, but is a process of business-related applications that have long been developing and implemented into ongoing feedback loops of human and machine interactions.
Going back to AI’s earlier business use days, back in 2005 the TAS Group launched the 1st predictive Sales Process Manager software application. It’s uncertain whether they called it “AI” at the time. Now based in Silicon Valley and known as Altify, the company has become a global leader in transformative sales methodologies, while its Co-Founder and Executive Chairman recently wrote a book on AI, which we’ll get back to momentarily.
Sales Process Management is built to use learned knowledge from millions of sales transactions, and combine that with information generated through your business’ activities to help you make decisions. Using Altify as an example, they have integrated it directly with the Salesforce system with a mind to provide you with advice on what to do next on a given day. As Altify describes it on their website: “By filtering the data for the important indicators – called Insight Signals – and interpreting what the signals mean in the business of sales, [we] can highlight vulnerabilities in a sale and provide intelligent coaching on how to approach the situation.”
(Spoiler Alert: “We don’t need to fear the robot overlords just yet, but we do need to decide how to use AI in business now.”)
Sometimes AI use cases are explicitly clear, other times not so much. Perhaps the most paradoxical business use for AI at the moment might be the pop-up virtual assistant messages that try to engage website visitors. Their goal is to provide sustained conversational interaction in order to keep potential customers on company’s landing page. While these virtual assistants use machine-generated responses to common questions based on Big Data analysis, which can lead to an “uncanny valley” effect when interacting with these non-humans.
“Siri, what is the uncanny valley?”
In aesthetics, the uncanny valley relates to human-like objects or mannequins that appear a bit too lifelike, and create an “eeriness” about them. [2] In conversations with virtual assistants, the interactions may seem a little too “real” for comfort… leading to questions such as to whether the assistant is a real person, overseas and on-call, whether there are the language or translation issues in play, or even how these assistants seem to know just a little too much information about you. However, most of these virtual assistants are simply there to help gather needed information in advance in order to get an actual telephone call directed to the proper (real) person.
One of the more powerful examples of such technology-based conversational tools for business is Cojito [3], which provides backend behavioural adaptation aimed to improve the emotional intelligence of real life customer support representatives. Rather than simply a virtual agent responding to context-driven key words in messages, Cojito offers a fusion of machine learning and behavioural science for improved customer interactions. The AI is blended right in to the efforts by telephone support professionals tackling the millions upon millions of voice calls that are occurring on a daily basis.
AI will be transformative, and already has been, even if it’s taking time to realize. As mentioned, Altify’s Donal Daly wrote a seminal work in 2016 on Artificial Intelligence called Tomorrow Today: How AI Impacts How We Work, Live, and Think (And It’s Not What You Expect) [4].
On the potential of AI on our work and day-to-day lives, Daly offers the following:
“The impact of AI in our personal and business lives is dramatic today and will be transformative tomorrow. Concepts like self-driving cars, smart homes, machine algorithms setting criminal sentencing guidelines, and the fear of jobs being replaced by AI are not something we can ignore. There are potentially fundamental economic and societal implications of which we must all be aware.”
So what are those implications, you may be asking? Well… there is a way to find out… Try: “Siri, I’d like you to search for a book by Donal Daly…”
