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Forbes
12 hours ago
- Business
- Forbes
Agentic AI In Enterprise QA: Powering Intelligent, Autonomous Testing At Scale
Pradeep Govindasamy is the Co-Founder, President and CEO of QualiZeal. We're at the beginning of a new era in quality engineering, one shaped by agentic AI. While generative AI has captured global attention, the real transformation in software testing is only just beginning. I believe we're now entering a phase where AI isn't just assisting people in testing tasks. It's becoming autonomous, goal-driven and capable of acting with intelligence across the lifecycle. At QualiZeal, we're witnessing this shift firsthand. As someone who has spent years in the testing space, I can confidently say that AI is not a far-off future. It's here, being built into our processes today, and it's already beginning to disrupt how we think about quality at scale. Software development and testing are the two most critical pillars in any IT application lifecycle. To get a product into the hands of customers, you first build it, then test it and only then can you ship it. We've seen how tools like GitHub Copilot have revolutionized development. Now, that same level of AI adoption is happening in software testing. This is no small market—it's a $100 billion global industry. And just as smartphones once disrupted legacy devices like BlackBerry, AI is poised to transform testing in a similar way. Every phase of the software testing lifecycle—test case preparation, test design, test data management, performance testing, site reliability engineering—is now being infused with AI to increase efficiency, productivity, and ultimately software quality. Before we talk about agentic AI, we need to understand the evolution. The first step in embracing AI is automating repetitive, rule-based tasks. Once you have robust automation in place, AI capabilities can be layered on top to improve every phase of testing. But agentic AI goes one step further. With standard AI, we build prompts, define logic and teach the models how to behave. With agentic AI, we create systems that learn, adapt and act autonomously. These agents follow instructions and understand intent. They can analyze changes in the system, adjust automation scripts accordingly and execute tests without human intervention. For example, imagine a scenario where a company updates its checkout process, maybe tariffs or payment options change. In the past, a QA team would have to manually identify changes, rewrite test scripts and rerun tests. With agentic AI, the system learns what's changed, modifies the scripts, self-heals when errors occur and continues testing. It even generates a report outlining what it changed and why. This self-healing, self-optimizing capability sets agentic AI apart from traditional automation. And it's a game-changer. We're seeing both technical benefits and measurable business outcomes. With agentic AI, the cost of quality is decreasing. From my observation, the industry average today is about 18%, but with AI-infused testing, we anticipate a 5% drop, driven by reduced manual effort and increased efficiency. In maintenance alone, we've seen a reduction from 20% of team capacity to less than 5%. Even more importantly, release cycles are accelerating. Time to market (TTM) has gone from quarterly to weekly, and now, with agentic AI and DevOps practices, to daily releases. The entire production throughput is becoming faster and more reliable. And decision-making is more seamless because agentic systems provide full transparency through real-time reporting, eliminating the need to compile data across disparate systems. Organizations looking to lead in this space must prepare now. I always say this moment is not just about catching up—it's about disrupting yourself before you get disrupted. Companies that wait too long will miss the opportunity to lead. Those who invest now will be in a position to capture market share and build the next generation of testing capabilities. This preparation requires both a top-down and bottom-up approach. Leadership must allocate budgets, not just wait for client-driven funding, and teams must be empowered to get trained, certified, and exposed to different AI models. AI isn't just a CIO or CTO conversation anymore. It's happening at the board level, and for good reason: this is the foundation for long-term competitiveness. I recommend organizations push their teams to reach at least level three in AI readiness: basic execution. Core functions like engineering and QA need to go further, while ancillary teams like finance and marketing should also gain exposure. Of course, with great power comes responsibility. We need to ensure agentic systems operate ethically, transparently and securely. Especially in regulated industries like healthcare, insurance or banking, any AI-driven decision, no matter how small, can have massive consequences. That's why testing the AI itself is just as important as using AI for testing. There's a growing demand for AI-specific test engineers who can validate agentic systems through high-end exploratory techniques. Traditional testing models like equivalence partitioning or boundary analysis must now be complemented with new approaches tailored to AI behavior. In the near future, eight to 10 new job roles will emerge specifically to test and validate agentic AI systems. These won't be optional. They'll be mission-critical. We estimate that full-scale AI maturity across the testing lifecycle will arrive around 2027. Between now and then, we're in the planning and education phase, training models, customizing LLMs and building the necessary infrastructure. Implementation will accelerate in 2026, and by mid-2027, I expect the majority of enterprise QA environments to be agentic by design. This is a once-in-a-generation opportunity for testers, developers and technology leaders. Gen Z professionals, especially those raised in a digital-native world, will have an edge. They can adopt these tools faster, and many will find themselves building careers in entirely new domains. We're not just building testing systems anymore. We're building trusting systems. Platforms that learn, adapt and support business continuity without human babysitting. That's the future of QA. That's where agentic AI takes us. And the companies that embrace it today? They'll be the ones defining quality tomorrow. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Forbes
02-06-2025
- Business
- Forbes
Multifamily Real Estate: How AI Is Powering Smarter Investments And Asset Management
Matias Recchia is Co-Founder and CEO of Keyway, the AI- powered real estate investment manager. getty If you're not using AI to power your multifamily real estate investments and operations in 2025, it's not too late to start. From market opportunity identification to tenant sourcing and retention to optimizing rental pricing, I've found that AI can provide a competitive advantage for real estate owners and operators through improved decision-making and meaningful investment returns. AI is not only streamlining operations but also fundamentally changing the way real estate stakeholders acquire, manage and scale real estate portfolios. Based on my own experiences as a real estate investment manager, here are three ways you can use AI to empower your team: AI can provide you with access to real-time, actionable data. For example, you can use it to identify a neighborhood with high growth potential early—based on income trends, job prospects, school quality and supply-demand characteristics—providing investors with an early look at where to allocate capital. AI can also analyze large datasets regarding demographic trends, economic indicators and competitor developments to provide a holistic view to investors. For example, you can use AI tools to ascertain in which neighborhoods rental demand is growing, which amenities will win more tenants in a particular city, and which neighborhoods are undervalued relative to those in comparable rental assets. Optimizing rental pricing is about maximizing occupancy and profitability for landlords in any market environment while simultaneously providing fairness and transparency to tenants. AI and machine learning can play an integral role in improving comparable property data, or comps, for commercial real estate. Traditionally, real estate teams have relied on manual processes to manage comps based on old data. But by leveraging AI and machine learning, you can reduce human error, manual labor and time. Furthermore, by relying on public data rather than landlord-reported private data, you can ensure that your real estate stakeholders have access to unbiased data with full transparency. Rent optimization also means landlords can price their units based on real-time data, reducing the likelihood of underpricing or overpricing. Real estate teams need multiple data points beyond gross rent to inform their rental pricing decisions. For example, rent trends, fee and concession trends, neighborhood dynamics, competitor pricing and economic indicators represent several components that comps platforms should analyze. You can also train your AI platform to incorporate cap rates and long-term appreciation potential to garner a more accurate picture of investment returns. Tenant screening is another component that can optimize both rent and occupancy. Consider using AI and machine learning to review applications, employment history, credit and other factors to predict whether a tenant will be reliable and financially responsible. With more reliable tenants, landlords can reduce turnover, which translates to higher recurring cash flow and occupancy. If you're a property manager, consider incorporating AI-powered energy management systems and offering automated tenant communications. You can also leverage AI to drive predictive maintenance. For example, AI can monitor HVAC equipment and elevators to determine when the next maintenance or repair is required so managers can avert major delays of services. By analyzing usage, useful life and prior maintenance work, you can proactively avoid tenant inconvenience, reduce complaints and save operational costs. Asset managers can leverage AI to deploy capital more systematically. For example, by sharing financial goals, investment returns and time horizons with your AI platform, you can better determine when to refinance assets, which assets should be prepped for sale and what's the optimal way to reinvest proceeds. Capital deployment optimization can be done in Excel, but I've found that AI reduces reliance on individual decision-making and takes a more objective approach. For example, my company uses an AI-powered program to manage our document workflow. Keeping track of leases, ensuring consistent lease terms and identifying inconsistencies in legal language are critical must-haves for any real estate team, and using AI tools instead of relying solely on your legal team can help reduce human error. When you have a clear lease management strategy, you can reduce legal costs and maintain consistency across your portfolio. I believe the future of multifamily real estate will be marked by dynamic pricing, predictive maintenance and AI-powered energy optimization. AI can give property owners and asset managers a real-time full view of their portfolio, which is important in a real estate market that is unpredictable and subject to economic and market fluctuations. By reducing manual errors, removing bias and creating uniformity in decision-making, real estate teams can have greater control over underwriting, operational roadblocks and tenant satisfaction, leading to an operationally sound multifamily market powered by technology, efficiency and data. Forbes Business Council is the foremost growth and networking organization for business owners and leaders. Do I qualify?
Associated Press
15-05-2025
- Business
- Associated Press
ByHeart Launches Anywhere Pack: A First-of-Its-Kind Travel-Ready Infant Formula for Modern Parents
NEW YORK--(BUSINESS WIRE)--May 13, 2025-- Today, ByHeart, the next-generation infant nutrition company, announced the launch of its newest product: the Anywhere Pack — a revolutionary, mess-free way to feed babies on-the-go. Compact, convenient, and pre-portioned, the Anywhere Pack offers freedom for parents to feed wherever life takes them. This press release features multimedia. View the full release here: ByHeart's innovation introduces a new single-serve option for modern parents specifically designed to simplify bottle-making while traveling, commuting, or tackling day-to-day errands. Each pack contains 14 pre-measured sticks of ByHeart's groundbreaking formula — the first infant formula in the U.S. to combine certified organic, grass-fed whole milk, their closest-to-breast-milk patented protein blend, and clinically proven benefits — now available in a flexible, travel-ready format. 'Today's parents aren't putting their lives on pause when they have children — they're bringing their babies along for the adventure,' said Mia Funt, Co-Founder and President of ByHeart. 'We created the Anywhere Pack specifically for this new generation of Beta babies whose parents are redefining what early parenthood looks like: more flexible, more mobile, and less tied to the constraints of home.' Key benefits include: 'At ByHeart, we're committed to advancing infant nutrition through breast milk science, evidence, and purpose. We created a formula that prioritizes baby's functional health and development, with breast milk as our north star. By focusing on powerhouse macronutrients such as protein, we've been able to create a patented protein blend that gets closest to breast milk,' said Ron Belldegrun, Co-Founder and CEO. 'With the Anywhere Pack, we're offering that same groundbreaking formulation in a new, convenient format — empowering parents to nourish their babies with optimal nutrition, wherever life takes them.' The Anywhere Pack is available for purchase now on ($19.99), and will be rolling out to retail partners nationwide, making premium infant nutrition accessible wherever families shop. To celebrate the launch of Anywhere Pack and its mission to help parents feed with freedom, ByHeart is giving away the chance to win 1 million airline miles to Generation Beta babies born between January and May 2025. Twenty lucky families will receive 50,000 miles each to support unforgettable first trips, honoring a major milestone in their parenting journey. From now until May 31st, parents of eligible babies can enter the giveaway on View source version on CONTACT: Press Contacts SGPR ([email protected]) KEYWORD: UNITED STATES NORTH AMERICA NEW YORK INDUSTRY KEYWORD: FDA RETAIL SMALL BUSINESS PROFESSIONAL SERVICES WOMEN TRAVEL PARENTING MEN FITNESS & NUTRITION CHILDREN BABY/MATERNITY FAMILY VACATION FOOD/BEVERAGE CONSUMER HEALTH SOURCE: ByHeart Copyright Business Wire 2025. PUB: 05/13/2025 10:03 AM/DISC: 05/13/2025 10:02 AM
