Every day, CIOs hear about solutions that can supposedly drive broader broad transformation and help them achieve greater business value. In the case of artificial intelligence (AI), it’s true. Or, rather, it can be true—if AI is approached correctly and embraced rapidly. And by rapidly, we mean organizations should be building or strengthening AI capabilities now.
Already, as many as 80 percent of all larger organizations are investigating AI, with up to 60 percent preparing to launch proofs of concept, according to one report. The implications for those that lag are not good—and the responsibility in large part rests with CIOs. According to Gartner, Inc., CIOs are “in the perfect position to educate the company’s CEO and board about recent developments in AI and illustrate how it might influence their business and their competitive landscape.”
For those choosing to pursue AI, the benefits can be substantial. Accenture looked at 12 economies and projected that by 2035, AI could boost profitability across 16 industries by an average of 38 percent. It will achieve this primarily through intelligent automation, labor and capital augmentation and through innovation. And, importantly, this move to boost profitability through AI is not prognostication. It’s happening now thanks to innovation by companies such as Salesforce.
How AI can drive improvements
First, AI can complement and enhance the skills and ability of existing workforces and physical capital. Second, it can create a new virtual workforce, in part through intelligent automation—which is smart enough, for example to even recognize and respond appropriately to human speech. And like any successful new technology, it can catalyze broad structural transformation by helping companies do things differently and do different things. This can work to kick–start profitability.
AI, which consists of multiple technologies that can be combined in different ways to sense, comprehend, act and learn, can only accomplish all this if organizations adopt a people–AI-collaborative mindset and take bold and responsible steps to apply AI technologies to their business. This involves letting employees move away from the mundane/routine, and establish a culture where there is capability to “raise” function specific AI to become a trusted part of the enterprise.
It starts, as outlined in this previous blog, with a decision is to move from a “what–if’ mentality to one of “do now.” The most efficient and productive wins are in ‘collaborative AI’ where people and AI cognition engines work together. Other than self–driving cars as an obvious example, Accenture has already begun helping clients apply ‘collaborative AI’: an oil field services corporation implemented a virtual agent to handle invoice inquires for finance and accounting procure–to–pay processing and a large casino company is tracking dealer performance, optimizing pricing and detecting play and betting fraud using computer vision, machine learning and deep learning methods.
In your CRM world
Salesforce.com’s AI offering, Salesforce Einstein®, makes AI accessible to their customers with clicks and code. Einstein’s capabilities span from out–of–the–box apps which bring AI to line of business users across sales, service and marketing, to deep learning APIs to help developers build smart apps, fast.
In the Salesforce Sales Cloud®, AI delivers industry insights and lead qualification/scoring, providing information around a client’s industry to help reps plan and execute campaigns. Salesforce’s AI also guides customer service agents, enabling them to focus on high–value activities and higher client satisfaction. It’s Salesforce Einstein Analytics capabilities provide predictive analytics and narrative reporting. Soon, we believe, Salesforce will use AI to automate financial results narratives, providing advice and analysis more quickly.
But in many ways, “soon” doesn’t apply because the technology is ready and proven. For a CRM cloud software company that wanted to implement the Einstein Analytics for executive and senior leaders, we created forward and backward–looking Forecast and Performance across multiple organizations. Based on predictive model algorithms, these capabilities are giving executives a better view of cross–organizational integrated, real–time information to make better business decisions.