Big tech as well as MSMEs are arming themselves with Artificial Intelligence (AI) in various forms. In August, Google parent Alphabet said it was expanding its AI-generated summaries for search queries to six new countries.
AI has become more profitable for companies to move by its sheer popularity. In July, Tesla reported its lowest profit margin in more than five years and missed Wall Street earnings targets in the second quarter. The reason, the electric vehicle maker has cut prices to revive demand while it increased spending on AI projects.
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Similarly, Zendesk launched an AI fund. Shopify introduced automation. Pinterest rolled out generative AI products to its advertisers. Target tested an in-store AI.
Most of the 38 startups that reached “unicorn” status this year have some sort of AI play. There’s plenty of cybersecurity, healthtech, and fintech, too. Among the mix are humanoid robots, Web3 social media, online drugs, genetic tests, fertility tracking, and a therapist finder.
AI experts are pointing out spaces that are potential markets for AI implementation. As per a survey conducted by Zycus and Procurement Tactics organizations can achieve a 10X efficiency boost in their procurement processes by adopting Gen-AI tools. It says nearly 70% of Chief Procurement Officers (CPOs) have yet to implement Gen-AI, highlighting a significant untapped opportunity for competitive advantage. Also, over 60% of companies lack specific policies on Gen-AI usage, underscoring the urgent need for strategic guidance as adoption accelerates.
AI is the new UI. How we engage with enterprise software is going through a fundamental transformation – from clicks to converse. Beyond this, GenAI – through AI agents is delivering significant productivity improvements across the entire source to pay cycle — Amit Shah, Chief Marketing Officer, Zycus
“AI is the new UI. How we engage with enterprise software is going through a fundamental transformation – from clicks to converse. Beyond this, GenAI – through AI agents is delivering significant productivity improvements across the entire source to pay cycle,” Amit Shah, Chief Marketing Officer, Zycus.
Already Dell CEO Michael Dell has predicted that AI PCs will be standard in the future.
With so much excitement in the AI realm, it’s no wonder that companies are scrambling to adopt the new technology. And those who haven’t are feeling left out.
According to Honeywell Industrial AI Insights, while only 17% of AI decision makers around the world have fully implemented their initial AI plans, more than 9 in 10 say they are uncovering unexpected new use cases whether they are in the prototyping, launch, or scaling stages of AI implementation. The research also finds they’re “sold” on AI for industrial applications. The enthusiasm for a deeper commitment to AI investment is nearly universal, with 94% of those surveyed saying they have plans to expand their utilization of AI.
With the advent of Gen AI and more sources of data from advanced analytics, Industrial AI is poised to grow exponentially, and the possibilities are endless for revenue growth and employee satisfaction — Kevin Dehoff, Honeywell’s Chief Strategy Officer
“There is no question that AI is currently at a pivotal moment,” said Kevin Dehoff, Honeywell’s Chief Strategy Officer. “With the advent of Gen AI and more sources of data from advanced analytics, Industrial AI is poised to grow exponentially, and the possibilities are endless for revenue growth and employee satisfaction.”
It seems every company out there is thinking about how to use AI, even though AI isn’t really making a lot of money for software companies yet. But the problem is that nobody is sure exactly how to use AI. This is creating a niche for consultants, who are profiting from AI FOMO. Work related to generative AI will make up about 40% of McKinsey’s business this year, according to The New York Times.
As per Honeywell research findings, 29% of Indian companies have already fully launched their AI strategy and 27% see data as their most important asset. In April, restaurant review company Yelp added video AI to create short narrated videos describing local businesses by collecting the photos, videos, and text descriptions uploaded to the platform by users.
AI companies like Qlik®, are enabling the integration of AI across industries, driving substantial business outcomes. For example, in digital marketing, RevLocal improved customer retention by 7% through predictive analysis using Qlik AutoML, highlighting the direct correlation between AI application and business growth.
In financial services, Integra leveraged Qlik’s AI for lead scoring and risk assessment in the loan process, projecting annual savings of over US$1 million, showcasing AI’s role in enhancing operational efficiency and profitability.
In terms of the use cases offered by the advanced technologies, 79% see improved efficiency or productivity and data availability to help decision-making as the most promising use cases for AI. In fact, 88% Indian enterprises expect to pay more to attract the right talent pool of AI engineers.
When asked for their thoughts on the impact of AI on industrials, AI leaders cite efficiency and productivity gains among the most promising benefits. 60% say improved cybersecurity and threat detection result from AI and 59% report better decision making due to real-time data generation.
With AI training and AI as a “co-pilot” the skills of a less experienced technicians can more quickly be upgraded, turning them into more elite experts that perform tasks based on enterprise knowledge and best practices. In turn, plants operations can run more safely and reliably by dramatically reducing human error — Lucian Boldea, President and CEO of Honeywell Industrial Automation
Lucian Boldea, President and CEO of Honeywell Industrial Automation, offered one direct example, “There can be tens of thousands of instruments, equipment and valves needed to process and manufacture a product and many of the parts we supply manufacturers require highly experienced technicians for operation and maintenance — and there are fewer and fewer of those experienced technicians available. With AI training and AI as a “co-pilot” the skills of a less experienced technicians can more quickly be upgraded, turning them into more elite experts that perform tasks based on enterprise knowledge and best practices. In turn, plants operations can run more safely and reliably by dramatically reducing human error.”
While the enthusiasm for AI to expand is palpable, there are still some challenges in the way of full adoption. Many feel that their C-Suite fully doesn’t understand how AI works and almost half say they are having to continually justify or request resources needed to implement AI plans.
All of this suggests the pace of change will be driven by compelling use cases that can be measured in terms of improved business performance. As new solutions demonstrate clear benefits to workforce productivity, safety, and reliability, AI adoption will dramatically increase with the potential to transform industrial operations.
Till then, according to a survey done by Qlik, while enterprises recognize the significant potential of unstructured data to enhance operational efficiency and drive meaningful insights, many are struggling to effectively leverage this resource.
Companies are looking for solutions that enable GenAI adoption without requiring them to overhaul their existing skillsets and technology stack. The opportunity is finding ways to integrate AI seamlessly into current analytics environments, allowing organizations to extract the right answers from unstructured data and drive meaningful business outcomes — Brendan Grady, General Manager of Qlik’s Analytics Business Unit
“With many sources citing that unstructured data makes up to 80% of the world’s data, it is no surprise that enterprise leaders want more real value from this untapped source,” said Brendan Grady, General Manager of Qlik’s Analytics Business Unit. “Companies are looking for solutions that enable GenAI adoption without requiring them to overhaul their existing skillsets and technology stack. The opportunity is finding ways to integrate AI seamlessly into current analytics environments, allowing organizations to extract the right answers from unstructured data and drive meaningful business outcomes.”
Organization leaders are concerned about data privacy and compliance concerns, significantly outweighing concerns about ROI (19%). Also, when evaluating vendors, system integration, cost, and governance features are top priorities, whereas vendor reputation seems to be a low priority.
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Interest in GenAI is high, but significant investment is lacking. Despite widespread interest, only 22% of all respondents indicate they are making “significant” investments in AI technologies.
Companies are rushing in to adopt AI even though many of them don’t fully understand how it works, and it hasn’t really increased ROI in a significant way. Yet many companies also hesitate to invest in this technology. The ones who are rushing in seem to be doing so only because they don’t want to be caught without it in case this technology turns out to be superstar everyone deems it to be.
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