Skill Gap Plagues AI Industry
AI adoption picks up in COVID-19, but skill gaps create low-code opportunities
Survey after survey are pointing out the increasing enterprise adoption of Artificial Intelligence (AI) & Machine Learning (ML); 57% of companies say they currently are using or are experimenting with the technology. The latest survey by 451 Research, now a part of S&P Global Market Intelligence, shows that AI & ML are an integral part of the enterprise digital transformation strategy.
There is a natural relationship between AI and digital transformation as the former is a means of producing the large-scale data analytics, insight and automation, all of which are goals of the latter. According to analyst firm Gartner, by the end of 2024, 75% of enterprises will shift from piloting to operationalizing AI, driving a 5x increase in streaming data and analytics infrastructures.
Enterprises are using a variety of strategies in their adoption of ML, but developing applications using cloud-based AI services seems the most popular at present with 48% in this segment, followed by those choosing to buy applications with ML built in (25%). More than half (51%) of enterprises have indicated that their current infrastructure cannot scale to meet future AI workload demands without considerable changes. According to IDC findings, by 2025, at least 90% of new enterprise applications will embed AI, and “over 50% of user interface interactions will use AI-enabled computer vision, speech, and natural language processing.
However, skill gaps in this transformative technology is continuing to hobble efforts to adopt AI across the enterprise value chain. All industry verticals have been scrambling to secure top AI talent from a pool that’s not growing fast enough. Even during the economic disruptions and layoffs caused by the COVID-19 pandemic, the demand for AI talent has been strong. Leaders are looking to reduce costs through automation and efficiency, and AI has a real role to play in that effort.
Deloitte’s third edition of the State of AI in the Enterprise survey found something unexpected when it came to skill gaps for AI implementations. Although a majority of the most mature AI adopters, the seasoned organizations, reported little or no gap between their AI needs and current abilities, 23 percent said they had a major or extreme one—a higher percentage than the less mature organizations. To cope with the skill shortage some organizations are turning to cloud-based platforms with pre-built solutions and accelerators.
According to Gartner by 2024, low-code application development will be accountable for more than 65% of app development activity. In the next 2-3 years, 75% of large businesses will be employing at least four low-code development tools for IT application development. Compared with the traditional software development method, low-code platforms help in much more deployment by deploying pre-built templates and automated software workflows which offer a simple way to build certain applications. The plug n play feature, and quick prototyping also helps expedite turnaround time for making simple applications. This market is already attracting the big names which are coming out with pre-configured AI solutions.
Microsoft and Adobe have announced the launch of C3 AI CRM powered by Microsoft Dynamics 365. The first enterprise-class, AI-first customer relationship management solution is purpose-built for industries, integrates with Adobe Experience Cloud, and drives customer-facing operations with predictive business insights.
The partners have agreed to integrate Microsoft Dynamics 365, Adobe Experience Cloud (including Adobe Experience Platform), and C3.ai’s industry-specific data models, connectors, and AI models, in a joint go-to-market offering designed to provide an integrated suite of industry-specific AI-enabled CRM solutions including marketing, sales, and customer service.
The partnership will sell the industry-specific AI CRM offering through dedicated sales teams to target enterprise accounts across multiple industries globally, as well as through agents and industry partners. They will target industry vertical markets initially including financial services, oil and gas, utilities, manufacturing, telecommunications, public sector, healthcare, defence, intelligence, automotive, and aerospace.
Earlier this year, a survey commissioned by intelligent automation vendor Kofax, “The Kofax 2020 Intelligent Automation Benchmark Study,” found that low-code platforms should improve efficiency across an organization. The survey of 450 automation and AI decision-makers worldwide found respondents believe that a low-code platform must result in reduced workloads (67%) and improve efficiency (70%). Respondents said such benefits are made possible when low-code platforms provide strong integrations with current technology (74%) and are easy to learn (73%) and use (71%). This is space to watch out for.
