We all know about the paradigm-changing use of AI for Netflix recommendations, chatbots that impersonate customer service agents online, and the dynamic pricing of hotel rooms. Such efforts are the value creation engines of countless large, successful companies. But organisations can also adopt a decidedly less splashy and, at face value, more pedestrian use of AI--to process documents faster and simplify operational procedures. Although this use is aimed at reducing costs rather than transforming industries, 'boring AI' is actually quite exciting--because it confronts issues that all companies wrestle with, and because the gains in productivity are real. Recent research by PwC on automating analytics found that even the most rudimentary AI-based extraction techniques can save businesses 30–40% of the hours typically spent on such processes.
Conversational AI solutions--including chatbots, virtual agents, and voice assistants--have become extraordinarily popular over the last few years, especially in the previous year, with accelerated adoption due to COVID-19. Data from various conversational AI vendors showed that the volume of interactions handled by conversational agents increased by as much as 250% in multiple industries.6 These solutions are already delivering significant value for many organizations. Around 90% of companies mentioned faster complaint resolution and over 80% reported increased call volume processing using conversational AI solutions, according to a recent survey.7 However, the technology still suffers from a number of limitations that make it difficult to use and limit its value.
The biggest challenge implementing artificial intelligence is moving from concept to scale. A new report from Deloitte finds that in consumer-related businesses, the challenge is especially difficult because many have large legacy data and analytics platforms, and decentralized data and analytics operations. Another common obstacle is achieving alignment and integration across business units and among IT stakeholders. These consumer businesses include consumer products, retail, automotive, lodging, restaurants, travel and transportation. Yet, "consumer-related businesses are actively exploring ways to harness the power of AI, and many valuable use cases are emerging,'' according to the report, The AI Dossier. However, AI adoption and maturity levels vary widely for reasons including scalability due to data quality and complexity, organizational constructs and talent scarcity, and lack of trust, the report noted. For each industry, the report highlighted the most valuable, business-ready use cases for AI-related technologies and examined the key business issues and opportunities, how AI can help and the benefits that are likely to be achieved. The report also highlighted the top emerging AI use cases that are expected to have a major impact on the industry's future. For example, in customer service, one of the largest segments of customer relationship management, it is now possible to personalize the customer experience across all channels, using machine learning, conversational AI and natural language processing through the customer journey and lifecycle, the report said. SEE: Digital transformation: A CXO's guide (free PDF) (TechRepublic) AI can help by automating customer interactions through the use of chatbots. It can also be used in tandem with Internet of Things devices to sense the sentiments and needs of connected customers and to personalize the customer experience, the report said. Consumer demand planning, forecasting and marketing will also be enhanced through AI, the report said. "As the number of sales channels used by consumers continues to grow, retailers should continue to improve how they plan across multiple sales channels--and how they handle disruptions.
Artificial intelligence (AI) is a constellation of technologies harmoniously enabling machines to act, learn and understand with human-like levels of reasoning. Maybe that's why everyone's definition of AI is different: It's so much more than just one thing. Machine learning and natural language processing are at the heart of AI. When paired with analytics and automation, these evolving innovations help companies improve customer service, optimize supply chains and achieve a seemingly endless number of business goals. And, fun fact, it can even help restore coral reefs.
Precision aligned with my personality and workstyle, but the idea of operating in a universe free of prejudice was even more exciting. As a young computer scientist, I was hyper aware of the potential for bias creep. I was often the only woman in the room. I experienced firsthand not being heard, counted or included. I hoped and believed that a mathematical approach to reasoning would neutralize the effect of people's unconscious biases.
Gartner predicts that "by 2022, 70 percent of white-collar workers will interact with conversational platforms on a daily basis." As a result, the research group found that more organizations are investing in chatbot development and deployment. IBM Business Partners like Sopra Steria are making chatbot and virtual assistant technology available to businesses. Sopra Steria, a European leader in digital transformation, has developed an intelligent virtual assistant for organizations across several industries who want to use an AI conversational interface to answer recurrent customer service questions. In developing our solution, we at Sopra Steria were looking for AI technology that was easy to configure and could support multiple languages and complex dialogs.
Three-quarters of government decision-makers struggle to select the right artificial intelligence solutions for their projects, a new report found. Still, 61% of respondents to a KPGM survey said AI is moderately to fully functional in their organization, according to "Thriving in an AI World," a report the professional services firm released March 9. And in the next two years, respondents said they plan to use AI to improve process automation (48%) and analytics (40%). To determine the best AI solutions, agencies must first define their use case, said Rob Dwyer, KPMG advisory principal specializing in technology in government. Robotic process automation is a common entry point to AI in the public sector because vendors in that area are well established, and it's relatively easy to earn small wins that can drive support for other AI efforts, he said.
The AI industry is playing a dangerous game right now in its embrace of a new generation of citizen developers. On the one hand, AI solution providers, consultants, and others are talking a good talk around "responsible AI." But they're also encouraging a new generation of nontraditional developers to build deep learning, machine learning, natural language processing, and other intelligence into practically everything. A cynic might argue that this attention to responsible uses of technology is the AI industry's attempt to defuse calls for greater regulation. Of course, nobody expects vendors to police how their customers use their products.
Apple's been on a shopping spree in a bid to make Siri smarter, according to a new report by GlobalData. The market research firm says the tech giant bought more AI companies than anyone else between 2016 and 2020. The second biggest AI acquirer was Irish consultancy Accenture. But the rest of the top five were all based in the US. Google grabbed the third spot on the list, followed by Microsoft and Facebook.