Latest news with #Java17
Time of India
12 hours ago
- Business
- Time of India
With AI on the rise, developer rates decline
Bengaluru: The 2025 Accelerance Global Software Outsourcing Trends and Rates Guide showed a global decline in software developer hourly rates, with decreases ranging from 9% to 16% across many regions. Tired of too many ads? go ad free now Latin America is the notable exception, where rates have remained steady. The report highlighted harder client negotiations, off-rate card deals, and cost takeout deals increasingly being offered by outsourcing partners to get projects over the line. Developer hourly rates declined across several key regions, with Eastern Europe seeing a 9% drop, and both South Asia and Southeast Asia experiencing steeper reductions of 16%. The 2025 edition of the report reviews data from 2024, comparing it to 2023 figures. It analyses median pricing across all software development roles, based on the latest survey results. This downward trend highlights a softening demand environment, driven by restrained enterprise IT budgets and increased discounting by software development firms competing for limited business in a crowded market. Peter Bendor-Samuel, founder and chairman of the Everest Group, said, "Over the last month, we are seeing much more aggressive pricing shifts than these as firms seek to capture the benefits of AI and are using AI aggressively with their internal teams, reducing the need for external support. The reason that Latin American rates are holding up is that in the new AI-driven apps world, time zone proximity is increasingly important, and we are seeing that translate into higher productivity, which in turn allows for higher or at least sustained rates. " Ray Wang, chief executive of Constellation Research, said AI has driven down the cost of software development. "In fact, we just saw a new firm, Soul of the Machine, headed by the legendary Sunil Karkera, beat out a major who bid a project with over 100 people and a 12-month timeline. Tired of too many ads? go ad free now He won a bid with less than 10 people in half the time. This is AI native scale." About 50% of Accelerance's respondents anticipate raising their rates by 1% to 5% within the next six months. This signals a departure from the double-digit growth in developer rates that defined the pandemic years. While inflation and ongoing shortages in high-demand tech roles will continue to drive price increases for some specialised skills, outsourcing providers are also offering more discounts and off-rate card deals. The integration of AI is reshaping various aspects of the software development lifecycle. Last year, Amazon CEO Andy Jassy announced a demonstration of the tangible value of the Amazon Q Developer agent for code transformation. With its help, Amazon successfully migrated tens of thousands of production applications from Java 8 or 11 to Java 17. This effort saved more than 4,500 years of manual development work across over a thousand developers and delivered performance gains amounting to $260 million in annual cost savings—underscoring the powerful impact of AI-assisted modernisation at scale. AI will play a much larger role in software development, with estimates suggesting that up to 70% to 90% of development tasks could be AI-driven by 2025 to 2027. Phil Fersht, CEO of HfS Research, said, "Our research shows 83% of US enterprises are increasing their investments in automation and AI because of the current tariffs and geopolitical instability." He said, "The market didn't twitch last Monday after Israel's attack on Iran, but I wonder what they will do on Monday, especially now the Strait of Hormuz is closed. . Trump's 90-day window on tariffs is also about to close with no real deals anywhere, and traditional 'big deals' business is very slow now in our industry."
Time of India
06-06-2025
- Business
- Time of India
Tech firms embrace agentic AI, drives faster code transformation
Tech companies are evaluating the benefits of deploying AI agents to augment developer productivity while broadening their GenAI implementation. These intelligent systems are being utilised across diverse functions, spanning from programming to systems transfer. Anupam Mishra, director of Developer Programs, AWS India and South Asia, said that these agents are successfully executing moderate-complexity coding assignments. Their functionalities extend to test case creation, documentation generation, security flaw detection, and solution development. At the recent AWS Summit Bengaluru 2025, Mishra informed TOI that his AWS teams achieved four times faster migration from .NET (pronounced dot net ) to Linux while working with clients. The cloud services company's product demonstrated an 83% quicker conversion of older Java scripts to newer versions for their client Persistent Systems. "We have a case study where several teams converted their Java code from older versions to newer versions. Amazon developers saved 4,500 years of manual work and $260 million annually from performance improvements by using our Amazon Q Developer Agent for code transformation to migrate over 30,000 applications from Java 8 or 11 to Java 17," he said. Mishra said the average time to upgrade an application to Java 17 plummeted from typically 50 developer days to just a few hours. "In under six months, Amazon upgraded more than 50% of its production Java systems to modernised Java versions at a fraction of the usual time and effort. Amazon developers shipped 79% of the auto-generated code reviews without any additional changes. As we use AI extensively, mundane tasks like writing test scripts will be taken away from the coder," Mishra said. Arun Parameswaran, EVP & MD of sales at Salesforce South Asia, said that agents generate 30% of code, expected to reach 50% by year-end. Their AI product for creating autonomous AI agents achieved 93% accuracy for a European airline client. For Salesforce's helpline, agents handle 84% of queries, with escalations reduced by half. Their CodeGenie model has processed over 7 million code lines, addressed 500,000 developer queries, and saved 30,000 monthly hours, enhancing developer efficiency and reducing costs. by Taboola by Taboola Sponsored Links Sponsored Links Promoted Links Promoted Links You May Like Giao dịch vàng CFDs với mức chênh lệch giá thấp nhất IC Markets Đăng ký Undo Cognizant earlier reported that agents write 20% of code, with plans to increase this proportion whilst passing AI-derived cost benefits to customers. US-based Constellation Research's principal analyst Ray Wang indicates that with agentic AI , code can be written using 20% of developers, achieving 50% higher productivity, while testing requires 40% fewer personnel. "We are seeing fully automated software development life cycles. In a world of exponential efficiency, IT services startups are delivering $1 million revenue per employee today and expect $5 million in 3 years," Wang said. IBM, in its proxy filing, said it achieved over $3.5 billion in annual productivity run-rate savings since 2022. Speaking at the IBM Think 2025 event in the US last week, its CEO Arvind Krishna said that in the long run, 'productivity is everything' and there is an 'insane need to go fast'. That is where agents come into play. According to Krishna, IBM's AI products Spyre and Telum, when used to detect fraud in financial transactions, could save $190 billion. Nasscom's recent GenAI report highlighted India's tech industry leading in agentic AI readiness, from vertical solutions in legal or pharmacovigilance processes to multiple platform-based use cases. AI Masterclass for Students. Upskill Young Ones Today!– Join Now
Forbes
04-04-2025
- Business
- Forbes
How Agentic AI Is Revolutionizing Security—And How To Keep It Safe
It's important to empower the future of automation with agentic AI, while safeguarding against ... More emerging security risks. One of the most promising developments in technology today is agentic AI—the evolution of AI tools that can perform complex, multi-step tasks autonomously and make contextual decisions with minimal human intervention. Unlike the standard generative AI models that have been the primary focus since ChatGPT came onto the scene, agentic AI is designed to operate independently, executing high-level commands and learning from its experiences. This capability holds immense potential across industries, from automating software development to revolutionizing cybersecurity operations. However, as AI systems begin to take on more autonomy, the security challenges they present must be addressed proactively. AI agents are no longer limited to simple, reactive tasks like text generation or code completion. They now possess the ability to execute complex workflows, adapt to new situations and make decisions on the fly. Itamar Golan, CEO and co-founder of Prompt Security, noted, 'Agentic AI differs from traditional GenAI tools in their ability to independently perform multi-step tasks and make contextual decisions.' This ability to autonomously complete tasks is not just a time-saver; it can fundamentally transform how organizations approach operations, particularly in IT and security. A prime example of agentic AI in action comes from Amazon Web Services, where AI agents were used to automate the transition of Java applications from older versions to Java 17. Chris Betz, CISO of AWS, explained, 'It's not just a recompile. You actually have to go through and rewrite the code to make it Java 17 compatible.' This process, which would traditionally require weeks of effort from developers for each application, was completed in a fraction of the time by leveraging agentic AI. These tools allow developers to focus on more innovative tasks, while AI handles the heavy lifting of routine updates and transitions. Betz estimated that AWS saved about 4500 years of developer work by going through building this tool. That said, the rise of agentic AI also introduces new risks, particularly around security and control. As Patrick Xu, co-founder and CTO at Aurascape AI, notes, 'With the advent of agentic AI, these technologies naturally become attractive targets for malicious actors. We can expect attackers to continuously innovate and devise novel ways to exploit AI-driven systems.' This new attack surface requires robust safeguards to ensure that AI agents operate securely within their designated tasks. While agentic AI promises significant operational efficiency, it also brings security risks that cannot be ignored. These risks stem from the AI's ability to execute actions without human oversight, its broad system access and its real-time decision-making loops. To mitigate these challenges, organizations must implement a comprehensive security framework. 1. Authentication and Authorization As agentic AI agents gain more responsibilities, ensuring strict control over what they can access is crucial. This means implementing proper authentication and authorization protocols to prevent unauthorized access to critical systems. According to Ariful Huq, co-founder at Exaforce, 'A critical enabler for secure, agentic AI is robust identity and permission management that establishes clear provenance for every action an AI agent takes on a user's behalf.' Ensuring that agents can only access the resources they need is key to minimizing potential security risks. 2. Output Validation One of the most critical components of AI security is output validation. Just as user input is considered untrusted until validated, AI-generated output must undergo rigorous scrutiny before being acted upon. AI systems, like any software, are prone to errors, and their autonomous nature means these errors can have widespread impacts if left unchecked. Proper validation ensures that AI outputs are reliable and aligned with organizational standards. 3. Sandboxing AI agents should never be allowed to execute code or perform tasks in a live environment without first being tested in a controlled, isolated sandbox. Sandboxing allows organizations to catch any errors or unexpected behaviors before they affect production systems. By implementing this practice, organizations can ensure that AI-generated actions are safe and do not pose a threat to the larger system. 4. Transparent Logging Transparency is essential for maintaining control over AI actions. Detailed logging of every step an AI agent takes allows security teams to understand how decisions are made and track any potential issues. This is particularly important for accountability and troubleshooting. 'When you have an AI agent, you want to know what it did and how it got there,' says Chris Betz. Detailed logs provide the insight needed to diagnose problems and improve security practices over time. 5. Continuous Testing and Monitoring Given the evolving nature of AI, continuous security testing is essential. Organizations should implement red-teaming and penetration testing to assess vulnerabilities within their AI systems and ensure they are resistant to new threats. As Ori Bendet, VP of product management at Checkmarx, highlights, 'With agentic AI, automated security is easy, securing the automation process is harder.' Ongoing testing and monitoring help ensure that AI systems remain secure as they evolve. As with all AI technologies, agentic AI raises important ethical concerns. One of the most pressing issues is the potential for AI to inherit biases from its training data. AI agents, when trained on biased or incomplete data, can make flawed or discriminatory decisions. In cybersecurity, for example, AI systems used to monitor network traffic or respond to incidents could potentially introduce new risks if they misinterpret their tasks or make biased decisions. Nicole Carignan, SVP at Darktrace, warns, 'Without proper oversight, agentic AI may misinterpret their tasks, leading to unintended behaviors that could introduce new security risks.' Organizations must remain vigilant in ensuring that AI agents are trained on high-quality, unbiased data and are regularly audited for fairness and accuracy. The autonomous nature of agentic AI means that these systems can be manipulated, much like human employees. Just as attackers use social engineering to trick people, AI agents can be tricked into executing malicious actions. Guy Feinberg, growth product manager at Oasis Security, points out, 'The real risk isn't AI itself, but the fact that organizations don't manage these non-human identities (NHIs) with the same security controls as human users.' Organizations must treat AI agents like human identities, assigning them appropriate permissions, monitoring their activity and implementing clear policies to prevent abuse. Despite their growing autonomy, agentic AI systems should be seen as tools that augment human capabilities, not as replacements for human oversight. While AI agents can handle repetitive and time-consuming tasks, human judgment is still required to ensure that outputs align with organizational goals and ethical standards. As Chris Betz notes, 'AI is here to make people go better and faster, not to replace them. It's about augmentation, not replacement.' For businesses to fully realize the potential of agentic AI, they must maintain a balance between automation and human oversight. By leveraging AI to handle routine tasks, organizations can free up human employees to focus on more strategic, creative and high-value work. Brian Murphy, CEO of ReliaQuest also stressed that agentic AI can automate many tasks, but human judgment will remain crucial. 'I personally do not believe we are ever going to separate a trained and skilled human in the last mile decision making.' The future of agentic AI holds tremendous promise. As these intelligent systems continue to evolve, they will drive innovation, improve efficiency and create new opportunities for organizations across industries. However, with this power comes significant responsibility. To fully harness the potential of agentic AI, businesses must implement robust security practices, maintain human oversight and ensure that ethical concerns are addressed. By doing so, they can unlock the transformative power of AI while safeguarding their systems against emerging threats. 'Agentic AI represents the next step in automating generative AI. As soon as humans become less prevalent, the risk of failure increases, but with proper safeguards in place, the benefits far outweigh the risks,' says David Benas, principal security consultant at Black Duck. With thoughtful security frameworks and responsible oversight, agentic AI has the potential to transform industries and redefine the way businesses operate—empowering a future where automation and human creativity work hand in hand.
