Tag: foundation models

  • Essential AI, GenAI, and Foundation Model Skills Reshaping Data Science Careers by 2026

    Essential AI, GenAI, and Foundation Model Skills Reshaping Data Science Careers by 2026

    Artificial intelligence is rapidly transforming the data science job market. A few years ago, most people associated the field with data scientists, analysts, and machine learning engineers. Today, the range of roles has expanded far beyond traditional expectations.

    According to the Analytics Insight Data Science Education Report 2026, new positions linked to generative AI, AI products, AI governance, and foundation models are emerging. These include GenAI Engineers, AI Product Managers, AI Governance Specialists, AI Solutions Architects, and Foundation Model Scientists. This shift also means the skills required for these jobs are evolving.

    The Rapid Growth of AI and GenAI Skills

    Generative AI has moved quickly from experimental projects to real-world business applications. Most companies now use AI for content creation, coding, or research. This growing adoption has created demand for professionals who can do more than just use AI chatbots. Businesses are looking for experts who understand and leverage these systems efficiently.

    For instance, GenAI Engineers work with large language models, data, AI applications, and testing. To streamline processes, they must understand how a model responds, where it can fail, and how its output can be improved.

    Prompt engineering has also gained popularity. Well-crafted prompts help AI tools produce clearer and more useful results. However, writing prompts is only part of the job. Professionals must also verify the accuracy of the output.

    Why does this matter? Because AI often makes mistakes. The report highlights that 56% of Indian companies see AI hallucinations as a challenge. An AI system may provide an answer that sounds correct but is actually wrong. This is why skills such as testing, fact-checking, and critical thinking are becoming increasingly important.

    Skills That Will Matter Most

    The report emphasizes that several technical skills remain essential, including machine learning, Python, big data, cloud computing, data engineering, deep learning, natural language processing, and computer vision.

    AI automation is also crucial. Many businesses want AI systems that handle routine tasks, helping employees save time. However, technical know-how alone is not enough. Professionals working with AI must be able to identify problems—whether poor data or models producing incorrect results. An AI system may behave differently when data or tasks change. In such cases, debugging and data-quality skills are vital for addressing issues.

    Responsible AI is another area gaining attention. Companies need people who can examine issues like bias, fairness, privacy, and how AI decisions are made. The report notes that nearly 51% of organizations have faced negative outcomes from unmanaged AI systems. It also points to a 53% talent gap in areas such as algorithmic bias audits and Explainable AI.

    The Road Ahead for AI Professionals

    The data science field is broader than it was a few years ago. AI and GenAI are creating new jobs and also transforming existing ones. For students and working professionals, the best approach is to build strong fundamentals. Machine learning, Python, data handling, and cloud skills still matter. These can then be combined with knowledge of GenAI, LLMs, AI automation, and foundation models.

    The Data Science Education Report 2026 shows where the market is heading. Future AI professionals will not just work with data; they will build AI systems, test them, fix problems, and help businesses use them responsibly.

    Frequently Asked Questions

    1. What are the most important AI skills in 2026? Machine learning, Python, cloud computing, data engineering, GenAI, AI automation, debugging, data quality, and critical thinking are among the top skills.
    2. What skills are needed for GenAI jobs? GenAI roles require knowledge of LLMs, AI applications, data, model testing, prompt design, and AI automation.
    3. What are Foundation Model skills? Foundation Model skills include understanding large AI models, testing their performance, adapting them for different tasks, and deploying them in real applications.
    4. Why is responsible AI important? Responsible AI helps companies address problems such as bias, privacy risks, unfair results, and unexplainable decisions.
    5. Will traditional data science skills still matter? Yes. Skills like Python, machine learning, statistics, and data engineering remain valuable. New AI skills build on these existing foundations.
  • Singapore AI Firm Sapiens Technology Makes Forbes Asia 100 to Watch List as Agnes Models Secure Independent Benchmarks

    Singapore AI Firm Sapiens Technology Makes Forbes Asia 100 to Watch List as Agnes Models Secure Independent Benchmarks

    SINGAPORE, September 9, 2026 — Sapiens Technology, the Singapore-based company behind the Agnes AI ecosystem, has been named to the 2026 Forbes Asia 100 to Watch list in the Enterprise Technology category. It is one of just 15 Singapore companies honored this year. Concurrently, its full-modality models have entered independent evaluation on the Artificial Analysis leaderboards, with Agnes 2.5 Pro Alpha debuting at #9 of 153 on the Intelligence Index.

    These twin milestones underscore the company’s mission: making frontier-grade AI capabilities accessible to developers and teams without the usual cost barriers.

    Forbes Asia 100 to Watch Recognition

    The annual Forbes Asia list recognizes privately held companies and startups across Asia-Pacific, selected on criteria including innovation, market fit, business model, growth, and industry impact. This year’s edition spans 100 companies across 16 countries and territories, with Singapore the second most-represented market after India. Forbes highlighted Sapiens Technology’s ability to train its own foundation models in-house across text, image, and video, as well as its progress with products including Agnes 2.5 Pro Alpha.

    Independent Benchmarking Across Modalities

    Agnes AI’s models have been independently evaluated on the Artificial Analysis leaderboards, providing developers with a third-party reference point per modality rather than relying on vendor claims. Agnes 2.5 Pro Alpha achieved #9 of 153 on the Intelligence Index and scored 58.8 on the Coding Index. Agnes-Video-2.5 was evaluated on the Text-to-Video Leaderboard, at $0.30 per minute of generated video.

    The pattern across modalities is consistent: independently measured capability priced for production, not just demos. Free API access lets developers test and integrate each model before they scale, and usage across the Agnes ecosystem now exceeds 8 trillion tokens per week.

    “A rank only matters if builders can afford to use what it measures,” said Bruce Yang, Founder of Agnes AI. “We put our models across every modality in front of independent evaluation, and priced them so a developer can put capable text, coding, image, and video into production without cost deciding what they get to try. The Forbes recognition tells us the bet is landing; the benchmarks tell developers it’s real.”

    About Agnes AI

    Agnes AI, developed by Singapore-based Sapiens Technology, builds full-modality foundation models across text, image, and video. Its mission is AI parity: making frontier-grade AI capabilities accessible to developers, startups, and teams building real-world products.

  • EXL Acquires iMerit to Bolster Enterprise AI with Foundation Model Capabilities

    EXL Acquires iMerit to Bolster Enterprise AI with Foundation Model Capabilities

    EXL (NASDAQ: EXLS), a global data and AI company, has announced a definitive agreement to acquire iMerit, a leader in AI model training, evaluation, and reinforcement learning. The deal, valued at up to $310 million, is expected to close in the third quarter of 2026, subject to customary conditions.

    The acquisition positions EXL at the forefront of enterprise AI innovation by adding iMerit’s direct relationships with foundation model builders. iMerit specializes in helping clients train large language and multimodal models to improve accuracy, precision, and effectiveness. By integrating iMerit’s capabilities with its own AI platforms—including EXLerate.ai, EXLdata.ai, and EXLdecision.ai—EXL aims to create a comprehensive end-to-end AI solution that moves enterprises from experimentation to production-scale deployment.

    “As organizations reimagine their businesses with AI, success requires industry-specific data, rigorous evaluation and reinforcement learning to deliver reliable results in business-critical workflows,” said Rohit Kapoor, chairman and CEO of EXL. “The acquisition of iMerit strengthens EXL’s AI strategy and ability to help clients move from experimentation to production. By combining iMerit’s capabilities with EXL’s domain expertise and AI platforms, we are setting the standard for AI that is trusted, accountable and built to perform in the enterprise.”

    iMerit brings two key assets to EXL: the Ango platform and the Scholars network. Ango enables sophisticated data interactions with generative AI models, supporting chain-of-thought reasoning, red teaming, and multimodal evaluations. Scholars expands EXL’s domain expertise through a global network of specialists—including physicians, scientists, engineers, linguists, and other subject matter experts—who provide human intelligence-driven feedback for reinforcement learning.

    These offerings will be integrated with EXL’s agentic platforms to combine expert human judgment, model evaluation, and enterprise-scale execution. The acquisition also expands EXL into high-growth AI sectors such as high tech, mobility, autonomous systems, and physical AI, leveraging iMerit’s expertise across text, image, video, voice, and LiDAR data.

    “We see EXL as an ideal leader in this defining moment for AI. We can build on our work with AI innovators and bring those insights to companies seeking to unlock their proprietary data,” said Radha Ramaswami Basu, CEO and founder of iMerit. “Both companies share a belief that specialized high-quality data is the foundation of AI success. We are excited to multiply our impact through EXL’s industry expertise, complementary technology and trusted enterprise relationships.”

    The transaction includes upfront consideration of $170 million, with an additional $140 million in incentives and earnouts over two years contingent on meeting specified milestones. The acquisition is expected to close in the third quarter of 2026, subject to regulatory approvals.