New research from Capgemini's Digital Transformation Institute shows that four out of five companies implementing AI have created new jobs as a result of AI technology Paris, September 7, 2017 – Capgemini, a global leader in consulting, technology and outsourcing services, has today announced the findings of "Turning AI into concrete value: the successful implementers' toolkit", a study of nearly 1,000 organizations with revenues of more than $500m that are implementing artificial intelligence (AI), either as a pilot or at scale. The research both counters fears that AI will cause massive job losses in the short term, as 83% of firms surveyed say AI has generated new roles in their organizations, and highlights the growth opportunity presented by AI: three-quarters of firms have seen a 10% uplift in sales, directly tied to AI implementation. The report, which surveyed executives from nine countries and across seven sectors, found that four out of five companies (83%) have created new jobs as a result of AI technology. Specifically, organizations are producing jobs at a senior level, with two in three jobs being created at the grade of a manager or above. Furthermore, among organizations that have implemented AI at scale, more than 3 in 5 (63%) said that AI has not destroyed any jobs in their organization.
'Organizations are pivoting towards operational analytics as it can both increase the efficiency and performance of the back office as well as boost the customer experience in the front office.' comments Anne-Laure Thieullent, Head of Big Data in Europe, for Capgemini's Insights & Data global practice. 'However, despite the focus, there are factors limiting the success of these projects; specifically siloed datasets, fragile governance models, inability to harness third party data sources, and an absence of a strong mandate from leadership teams.' 'Going Big: Why Organizations Need to Focus on Operations Analytics' from Capgemini Consulting's Digital Transformation Institute mapped organizations based on the extent to which their analytics initiatives were integrated with core operations processes and their success rate with initiatives, identifying four stages of operational analytics maturity: Capgemini Consulting's Digital Transformation Institute applied the four stages of operational analytics maturity to build up a geographic picture of adoption and success rates around the world. US companies are not only the most advanced with their analytics initiatives but also the most successful; 50 percent have successfully realized the desired benefits from operational analytics compared to only 23 percent of Chinese respondents, despite China ranking highly for level of implementation. A strong contributing factor of the success of US companies is their focus on setting up effective data and governance processes. The prominence of US organizations tallies with a recent resurgence in US manufacturing and will drive US manufacturing competitiveness in the coming years.
Businesses are increasing the pace of investment in AI systems to defend against the next generation of cyberattacks, a new study from the Capgemini Research Institute has found. Two thirds (69%) of organizations acknowledge that they will not be able to respond to critical threats without AI. With the number of end-user devices, networks, and user interfaces growing as a result of advances in the cloud, IoT, 5G and conversational interface technologies, organizations face an urgent need to continually ramp up and improve their cybersecurity. AI-enabled cybersecurity is now an imperative: Over half (56%) of executives say their cybersecurity analysts are overwhelmed by the vast array of data points they need to monitor to detect and prevent intrusion. Accordingly, almost half (48%) said that budgets for AI in cybersecurity will increase in FY2020 by nearly a third (29%).
Although AI offers vast implications for engineering, production, supply chain, customer experience, and mobility services, progress in AI-driven transformation has been sluggish and uneven due to lingering roadblocks. The number of automotive companies deploying AI at scale has grown from 7% in 2017 to 10% today, with OEMs generally making better progress than suppliers or dealers. Geographically, the US, where 25% of companies implement AI at scale, is leading the way in terms of progress, followed by the UK (14%) and Germany (12%). In terms of pronounced growth, China is making huge strides, having nearly doubled its share of scaled AI implementations, from 5% to 9%. The new report by the Capgemini Research Institute, Accelerating automotive's AI transformation: how driving AI enterprise-wide can turbo-charge organizational value, surveyed 500 executives from large automotive organizations in eight countries and interviewed a number of industry experts and entrepreneurs to understand how progress in deploying AI at scale can be accelerated.
The first idea that likely springs to mind when you think about artificial intelligence and cars is autonomous driving. But the auto industry has many other uses for AI: Collecting and parsing safety data, and design, to name just two. Given the hype around the opportunities presented by intelligent machines, we might expect that segment of the industry to be booming. Like a host of other industries where leaders want to explore and employ AI but can't, there just aren't enough people to hire. Car companies globally aren't progressing AI projects nearly as fast as trends suggested they would two years ago, according to a report released last month by the Research Institute of Capgemini, a global consultancy firm.