Business

Agentic AI: 9 promising use cases for business

Published

3 months ago

June 19, 2025

That’s the way it was done in the past, until gen AI came along. Human experts now enhance reports generated by AI.

“Now we can feed AI all the contact and public documentation, and it can spin out a report in minutes instead of days with tremendous accuracy and detail,” he says. “AI plus human expertise is a tremendous boost in quality,” he says.

Now, with AI agents, the process is changing yet again. EY will release an agent-drive version of the process to evaluate vendors. “It’ll be a continuous monitoring of vendors, which was previously not possible,” Schuller says.

AI agents aren’t just about optimization use cases, he adds. “The real value is this expansion of the market, and expansion of revenue opportunities.”

HR and employee support

Another relatively low-risk, high-value use case for AI agents is answering employee questions and handling simple tasks on their behalf. A January IBM survey on gen AI development, in fact, concluded that 43% of companies use AI agents for HR.

Indicium, a global data services company, began deploying AI agents in mid-2024, for example, when the technology started to mature.

“You’d start seeing off-the-shelf applications — both open source and proprietary — that made it easier to build them,” says Daniel Avancini, the company’s CDO.

The agents are used to making things easier for HR, he says, including tasks such as internal knowledge retrieval, tagging, and documenting, as well as other business processes.

Each agent is like a microservice, specializing in one particular thing. “And they all talk to each other in a multi-agent system,” he says.

And these prompt-based conversations can get peculiar. The tricky thing is there’s a possibility of hallucinations and all the other problems that come with gen AI. “So there’s a lot of tweaking of the model so they don’t do the wrong thing or access the wrong information,” he says.

On the positive side, the AI agents can handle a lot of questions autonomously, creating a another business benefit. “And we’re finding things that aren’t correctly documented, so it helps us make the processes better,” Avancini adds.

Business intelligence

Another area where AI agents will have a large impact is business intelligence. While BI dashboards are relatively simple to use, gaining insights that go beyond the standard categories has often taken the work of a data team to extract, says Ryan Janssen, co-founder and CEO at Zenlytic, an AI-powered BI vendor.

An AI agent paired with a BI solution could give more employees access to useful analytics, he says. For example, an AI agent for BI could advise a marketing team about where to spend its budget or create a chart based on an example drawn on a napkin, Janssen says.

AI agents that understand voice inputs can generate business data insights based on spoken questions such as, “What are our top three marketing channels?”

“That’s a very natural question, but it’s ambiguous,” Janssen says. “What you can’t do with the chatbot versus an agent is disambiguating that ambiguous question. What do you mean by ‘top’? The agent, when well built, will say, ‘Oh, wait, this is ambiguous; I need to go back and use a tool for this.’”

Many organizations are just at the start of their agentic AI journeys, and there are hundreds of uses yet to be discovered, Janssen adds. Coding agents are an early use case because programming is detail-driven and time consuming, but now coding hobbyists are building apps using coding assistants.

“The way that they are best applied is when you have work that is grindy, takes a lot of work, or requires a lot of attention to detail,” Janssen says.

When dozens of agents get strung together and organized, enterprises will see new breakthroughs, he adds.

“We haven’t even scratched the surface yet with what agents can do,” he says. “We don’t know what an organization looks like yet, how they’re supposed to interact, and how it is governed. But I have no doubt that over the next couple of years, we’re going to figure that out.”

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Business

i.AI: Paving the Way for India’s Global Digital Footprint

Published

21 minutes ago

September 4, 2025

Devdiscourse News Desk

New Delhi, India – i.AI, a pioneering social media platform from India, is revolutionizing the digital economy by embodying the Prime Minister’s vision of self-reliance. The platform is more than a social channel, establishing a robust ecosystem that engages creators, businesses, and users with AI while safeguarding and monetizing Indian data domestically.

Founder and CEO Kapil Agarwal asserted that i.AI responds to the call for creating homegrown digital solutions. With a target revenue of over Rs.500 crore in the next 24-30 months, the platform aspires to achieve breakeven operationally by the third year. Supported by cultural relevance and AI innovations, i.AI aims to emerge as the nation’s first global social media export.

The platform continues to engage users by promoting regional content and empowering creators, marking it as a formidable competitor to global players like Facebook and Instagram. Future expansion across Asia, the Middle East, and Western markets seeks to enhance India’s position in the global digital landscape, merging technology and culture.

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Business

Peter Kyle pushes for AI regulation overhaul to boost UK business

Published

2 hours ago

September 4, 2025

Computing Staff

£2.7 million government fund for regulation reforms

Speaking at Mansion House yesterday, Technology Secretary Peter Kyle announced a £2.7m fund for AI regulation reforms, aiming to speed up innovation while ensuring oversight and boosting the UK’s tech competitiveness.

Technology Secretary Peter Kyle has unveiled a package of measures aimed at reshaping the UK’s approach to AI regulation.

Kyle has been vocal about AI policy in recent months, previously urging UK workers to embrace AI or risk falling behind.

Speaking at Mansion House on Wednesday, Kyle announced a £2.7 million government fund to help regulators pilot AI systems across sectors, including energy, aviation and nuclear oversight. The move forms part of a wider push to reduce regulatory burdens and position Britain as a global centre for AI investment.

“We want you to keep investing here, keep building here, list here, scale here. If you invest in Britain, you’ll share in that competitive edge,” Kyle said.

Support for regulators and new AI industry standards

The funding will back initiatives such as Ofgem’s development of AI tools to speed up clean energy approvals, the Civil Aviation Authority’s use of AI to analyse air accident reports, and projects to improve nuclear waste management. Kyle says the aim is to fast-track approvals, cut delays, and support safe adoption of new technologies.

Alongside the regulator fund, the government confirmed plans for what it calls a “dedicated AI assurance profession”, supported by an £11 million innovation fund. The assurance roadmap sets out the creation of professional standards, ethical codes, and certification schemes to oversee AI deployment.

Stuart Harvey, chief executive of Datactics, welcomed the government’s direction on AI innovation, saying: “Peter Kyle’s call for AI reform is a welcome step towards making AI regulation more responsive to business needs. Too often, innovation is slowed not by lack of ambition, but by unclear governance and fragmented oversight. Creating space for innovation through AI-specific regulatory sandboxes and improving access to technical infrastructure would be a meaningful shift…”

Balancing growth with oversight

This latest pledge is tied to record levels of private AI investment in the UK, with £2.9 billion channelled into the sector last year.

It comes amid ongoing debates over the government’s AI policy direction, including recent changes to the AI Safety Institute.

Amid AI safety concerns, the Labour government has been exploring various ways to boost UK AI adoption, including discussions of a national ChatGPT subscription deal.

Senior vice president international at Absolute Security, Andy Ward, urged the government to tread with caution. “AI offers huge promise to improve detection, speed up response times, and strengthen defences, but without robust strategies for cyber resilience and real-time visibility, organisations risk sleepwalking into deeper vulnerabilities,” he noted.

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Business

Memories.ai Founder Offers $2 Million Packages to Poach AI Researchers

Published

2 hours ago

September 4, 2025

Rosalie Chan

Shawn Shen is the 28-year-old cofounder and CEO of Memories.ai, a startup that builds AI to see and understand visual data. He got a Ph.D. at the University of Cambridge before joining Meta as a research scientist. Late last year, Shen left Meta to launch his startup, raising an $8 million seed round this summer backed by Samsung and others.

Meta has supercharged the Silicon Valley talent wars by making staggering, nine-figure offers for some AI researchers and starting a new AI unit, Meta Superintelligence Labs. That’s sparked tensions in its sprawling AI operations, with some Meta staff leaving.

Memories.ai announced Thursday that it’s offering up to $2 million compensation packages for researchers from Meta, Google, Microsoft, Anthropic, xAI, and others. It also recently hired Chi-Hao Wu, a former Meta research scientist, as its chief AI officer.

This is an as-told-to essay based on a conversation with Shen. It has been edited for length and clarity. Meta and Microsoft declined to comment. Google, OpenAI, xAI, and Anthropic didn’t respond to requests for comment.

Why I’m offering AI researchers $2 million

It’s because of the talent war that was started by Mark Zuckerberg. I used to work at Meta, and I speak with my former colleagues often about this. When I heard about their compensation packages, I was shocked — it’s really in the tens of millions range. But it shows that in this age, AI researchers who make the best models and stand at the frontier of technology are really worth this amount of money.

We’re building an AI model that can see and remember just like humans. The things that we are working on are very niche. So we are looking for people who are really, really good at the whole field of understanding video data.

We’re not worried about running out of money

We are welcoming people who want to take more equity compared to cash, which means that it won’t shrink our runway by a huge amount. The exact cash-versus-equity split will depend on the person we hire. We will treat these hires as founding members, not as employees. Anyways, equity is where you can get a hundred or even a thousand times return in the future.

We are thinking of hiring three to five people in the next 6 months, and another five to ten in the next 12 months. We plan to raise more money, too.

Spending so much on talent will help, not hurt, our fundraising

As long as we have the ability to consistently attract top AI talent, raising additional capital will not be a problem. The capital markets are eager to back companies that can do this. Just look at how much Thinking Machines Labs has raised or how much Fei-Fei Li’s startup has raised. As long as an AI company can recruit the best AI people, they can really just go through any kind of economic period.

Meta’s constant reorgs help our hiring efforts

Meta is constantly doing reorganizations. Your manager and your goals can change every few months. For some researchers, it can be really frustrating and feel like a waste of time. So yes, I think that’s a driver for people to leave Meta and join other companies, especially startups.

There’s other reasons people might leave. I think the biggest one is what Mark (Zuckerberg) has said: in an age that’s evolving so fast, the biggest risk is not taking any risks. So why not do that and potentially change the world as part of a trillion-dollar company?

We have already hired Eddy Wu, our Chief AI Officer who was my manager’s manager at Meta. He’s making a similar amount to what we’re offering the new people. He was on their generative AI team, which is now Meta Superintelligence Labs. And we are already talking to a few other people from MSL and some others from Google DeepMind.

I learned a lot of great things from Meta

I definitely learned a lot from Meta because Meta is very bottom-up. So you see a lot of innovations across different departments. Things like multimodal, visual, and super-personalized AI — everyone is so open to talking about their ideas. I met with so many talented people. I made an effort to meet three to four of them every week to talk about our hobbies and future goals.

It really shaped my future and gave me a clear road map. But in the end, the reason I left Meta is that I wanted to start a great company.

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