New specialisation within Master of Science in Accounting focuses on applying, evaluating and governing Generative and Agentic AI in accounting and finance

SINGAPORE, Oct. 7, 2026 /PRNewswire/ — The accountant of the future may spend less time checking documents and more time checking what artificial intelligence has done with them.

AI is already being used in accounting and finance to review documents, analyse financial information, identify anomalies and support audit work. But as more of this work is performed or assisted by AI, professionals still have to decide whether its outputs are accurate, appropriate and reliable enough to inform a business decision.

Singapore Management University’s (SMU) School of Accountancy (SOA) is responding to this shift with a new Applied Artificial Intelligence Track in its Master of Science in Accounting (MSA) programme. The track is designed to equip accounting and finance professionals with the skills to apply AI to professional workflows, evaluate its outputs and put appropriate governance and human oversight around its use.

The move comes as AI is reshaping the work of accounting and finance professionals. Budget 2026 identified accountancy as one of the professions where AI can automate routine work and enable professionals to focus on higher-value activities requiring professional judgement and expertise. The Government also announced that it would support workers in building practical AI capabilities, starting with the accountancy and legal professions.

An accounting-first approach to AI

Unlike AI programmes centred primarily on computer science, data science or general business applications, the new track starts with the professional contexts in which accounting expertise matters.

Students will gain practical exposure to technologies including Generative AI, large language models (LLMs), retrieval-augmented generation (RAG) and Agentic AI. They will learn not only how these technologies can be applied, but also how to assess their reliability and limitations, supervise AI-enabled workflows and establish appropriate controls.

The emergence of Agentic AI extends this shift beyond generating content and analysis towards AI systems capable of coordinating and executing multi-step workflows. For accounting and finance professionals, this raises new questions about how such systems should be supervised, where human review and escalation should occur, and who remains accountable for the resulting decisions.

Professor Zhang Liandong, Dean and Lee Kong Chian Professor of Accounting, SMU School of Accountancy, said:

“We designed the Applied AI Track around how AI is entering accounting and finance work. The question is not simply whether a tool can perform a task, but whether professionals understand its limitations, can evaluate its output and know what controls are needed before relying on it. Students will therefore learn to apply emerging technologies such as Generative and Agentic AI within professional workflows, while retaining the professional judgement, human oversight and accountability that remain central to the profession.”

The Applied AI specialisation comprises four Course Units drawn from five specialist offerings, covering Agentic AI for Accounting; AI Governance, Evaluation and Ethics; Modern AI Applications in Business; Blockchain and AI for Decentralised Intelligence; and the Innovation and Technology Capstone (SMU-X).

The curriculum combines these specialist courses with the MSA’s accounting core and foundational training in programming, data management, statistics, forecasting, visual analytics and machine learning. Through the SMU-X capstone, students will also apply AI, analytics and digital technologies to real accounting and finance problems with industry partners.

The track is built around the premise that AI should augment rather than replace professional expertise. Its emphasis is on applied use, evaluation and governance of AI in professional contexts, rather than on developing AI models from the ground up. Students will learn to integrate AI into existing workflows, establish review and escalation points, evaluate AI-generated outputs and determine where human intervention remains necessary.

From using AI to governing it

The capabilities developed through the track extend beyond learning to operate AI tools.

Graduates will be equipped to apply, evaluate, supervise and govern AI in professional contexts, including the ability to:

apply AI to accounting, audit and assurance, financial analysis, finance transformation and related professional workflows;evaluate AI-generated outputs and identify inappropriate assumptions, errors or limitations;design and supervise AI-enabled workflows, including human-in-the-loop processes;assess risks relating to privacy, cybersecurity, model risk, bias, explainability and regulatory compliance; andtranslate AI-generated insights into decisions that remain subject to professional accountability.

Ms Irene Liu, Managing Director, Risk, Regulatory and Compliance Lead for Southeast Asia, Accenture Southeast Asia said: “Firms are starting to use AI across finance, from reconciliations and detection of potential reporting issues to correcting journals and supporting complex financial valuations. As AI becomes embedded in finance systems and workflows, accountants increasingly need to understand how to interact with these AI tools, validate their outputs, identify exceptions and exercise professional judgement over when and how those outputs should be used.”

This shift could affect a wide range of professional work, from audit working-paper and document review to financial analysis, anomaly and risk detection, finance-process redesign and controls over AI-generated outputs.

The track is intended to prepare professionals who can apply, evaluate, supervise and govern AI within their area of expertise, rather than simply use AI tools.

Building on an established accounting and analytics foundation

The Applied AI Track builds on the MSA’s existing focus on data and analytics. The MSA comprises 15 Course Units, including eight programme core courses, four track electives, two open electives and one postgraduate professional development course.

Students may also use their open electives for an internship, other SMU master’s courses, or overseas immersion and exchange opportunities.

As AI takes on more of the work traditionally performed by professionals, the role of the accountant will continue to evolve. Knowing how to use AI will be one part of that change. Equally important will be knowing when to question it, when not to rely on it, and who remains accountable for the decisions that follow.

About Singapore Management University (SMU)

Established in 2000, Singapore Management University (SMU) is recognised for its high-impact, multi-disciplinary research that addresses Asian issues of global relevance, and for its interactive, collaborative and project-based approach to learning. Home to over 13,000 students across six schools and two colleges, SMU offers bachelors, masters and PhD programmes across Accountancy, Business, Economics, Information Systems, Integrative Studies, Law and Social Sciences, as well as executive development and continuing education programmes. SMU graduates are consistently ranked among the most employable in Singapore, and command one of the highest mean starting salaries. Through its city campus, SMU enjoys strategic linkages with business, government and the wider community in Singapore and beyond.
www.smu.edu.sg

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SOURCE Singapore Management University

Chandigarh University’s CUBIC becomes India’s First University-Led Quantum Incubator for Deep-Tech Startups, Signs MoU with 247VC

NEW DELHI, Oct. 7, 2026 /PRNewswire/ — Chandigarh University’s CUBIC, India’s first university-led quantum incubator for deep-tech startups became an academic and incubation partner for PRAGATI Q-Foundry 2026, a national initiative of the Ministry of Science and Technology, aimed at accelerating the development and commercialization of quantum technologies, and signed a Memorandum of Understanding (MoU) with 247VC Investment Trust which is a leading Indian venture capital firm on the sidelines of the PRAGATI Q-FOUNDRY 2026 NQM Co-development and Venture Partnership Meet held on September 29–30 in New Delhi.

The MoU will facilitate direct access to potential investment opportunities, strategic mentorship and business support for quantum and deep-tech startups associated with CUBIC. The national meet was addressed by the Union Minister of State for Science and Technology and Earth Sciences, Dr. Jitendra Singh, and brought together startups, academic institutions, industry, investors, manufacturers to accelerate the translation of quantum technologies from research towards validation, co-development, commercialization and deployment under India’s National Quantum Mission (NQM).

The MoU with 247VC Investment Trust adds an investment and business-development dimension to CUBIC’s incubation activities. This collaboration aims to help promising startups associated with CUBIC access potential seed-stage and eligible early-stage funding opportunities to strengthen investment readiness and connect to relevant investor networks. Under this agreement, CUBIC may identify suitable startups from its incubation ecosystem and facilitate introductions to 247VC, subject to the investor’s sector preferences, stage requirements and investment criteria.

The agreement also provides for potential investor–startup interactions through pitch sessions, curated meetings, demo days and other mutually agreed platforms. CUBIC may support eligible startups in preparing business plans, pitch decks, financial projections and technology and intellectual property documentation required for fundraising. Where mutually agreed, 247VC or its representatives to provide strategic mentorship in fundraising, business development, commercialization and market access.

The parties will also explore opportunities to connect eligible startups with venture capital funds, angel investors, family offices, corporate investors and strategic partners. Potential follow-on investments may be considered for selected ventures as they progress through subsequent stages of growth and fundraising, subject to 247VC’s independent evaluation, due diligence, investment mandate and internal approvals. The MoU establishes a framework for collaboration but does not guarantee funding or create an obligation for the investor to invest in any startup.

Jai Inder Singh Sandhu, Managing Director, Chandigarh University, said, “PRAGATI Q-FOUNDRY 2026 highlights the importance of connecting academic research with industry, investors and strategic users so that promising technologies can move closer to practical applications. Through CUBIC’s role as an academic and incubation partner, Chandigarh University aims to contribute by bringing together research capabilities, emerging talent and entrepreneurial innovation in quantum and other deep-tech domains. Our MoU with 247VC complements this effort by creating a structured pathway for eligible startups to engage with potential investors, strengthen their investment readiness and access strategic mentorship.”

Sandhu added, “For the National Quantum Mission to translate into lasting technological and economic value, India needs to connect scientific research with technology validation, industry adoption, investment and entrepreneurship. Universities can contribute by nurturing talent, supporting research-led innovation and helping promising ideas progress towards commercially viable solutions. Through these collaborations, we aim to strengthen the connections between research, incubation and investment and support India’s broader ambition of developing indigenous, globally competitive technologies.”

The CUBIC will help connect academic knowledge, research capabilities and emerging entrepreneurial ideas with opportunities for technology development and industry engagement. The association will create avenues for students, researchers, faculty members and aspiring entrepreneurs to engage with stakeholders working in quantum technologies and other frontier domains. The initiative aligns with the broader objectives of the National Quantum Mission, which seeks to strengthen indigenous capabilities in quantum computing, quantum communication, quantum sensing and metrology and quantum materials and devices.

PRAGATI Q-FOUNDRY 2026 provided a national platform for academic and research institutions to showcase promising technologies, connect with strategic users and investors and explore technology transfer, co-development and deployment opportunities. By participating in this initiative, CUBIC aims to strengthen the link between university-led research and practical technology applications, supporting the progression of promising ideas towards deep-tech ventures. Its areas of interest extend beyond quantum technologies to include semiconductors, photonics, advanced materials, robotics and artificial intelligence.

Chandigarh University

Chandigarh University is a NAAC A+ Grade University and QS World Ranked University. This autonomous educational institution is approved by UGC and is located near Chandigarh in the state of Punjab. It is the youngest university in India and the only private university in Punjab to be honoured with A+ Grade by NAAC (National Assessment and Accreditation Council). CU offers more than 109 UG and PG programs in the field of engineering, management, pharmacy, law, architecture, journalism, animation, hotel management, commerce, and others. It has been awarded as The University with Best Placements by WCRC.

Website address: https://www.cuchd.in/

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Simplicity AI SDK with new Simplicity Design Intelligence, open-source development, and Databricks initiatives help developers build faster and bring edge AI into enterprise workflows

AUSTIN, Texas, Oct. 7, 2026 /PRNewswire/ — Works With Summit 2026 – Silicon Labs (NASDAQ: SLAB), the leading innovator in low-power wireless connectivity, today announced a set of developer initiatives that makes it easier to build, extend, and operate increasingly capable IoT devices. Unveiled at the company’s seventh annual Works With Summit, the new offerings expand what developers and their AI agents can create on the Silicon Labs platform, while helping customers develop, deploy, and manage intelligence at the edge.

News at a Glance

Design with AI: The Simplicity AI SDK is now in public Beta and supports AI coding assistants including GitHub Copilot, Cursor, and Codex. Silicon Labs is also introducing Simplicity Design Intelligence, a broad and growing set of capabilities designed to understand hardware and software intent, help customers turn that intent into a working product, and verify the implementation against the original intent. Hardware Intent is the first capability.

Build and extend: The Silicon Labs open-source community is launching in Beta with Bluetooth® Low Energy (LE), giving developers access to sample applications and tooling and a direct way to raise issues, propose fixes, contribute code, and extend the Silicon Labs software platform.

Scale edge intelligence: Silicon Labs’ platform-agnostic edge AI and machine learning tools can now connect with Databricks, the data and AI company, so customers can manage data, models, embedded optimization, and hardware test results with governed enterprise data and AI workflows on the Databricks Data + AI platform.

Development Complexity Cannot Scale with IoT

As connected products add intelligence and custom hardware, building them grows more complex. Developers navigate specialized SDKs, configuration tools, debugging environments, and hardware constraints while using general-purpose AI assistants that do not inherently understand Silicon Labs devices or embedded workflows. Development teams also need better ways to share improvements and manage AI models as intelligence moves from the cloud onto edge devices. If workflows become harder with every new capability, development complexity becomes a barrier to scaling IoT.

“More capable silicon should not create more development complexity,” said Manish Kothari, Senior Vice President of Software at Silicon Labs. “We are giving developers and their AI agents a connected path from hardware and software intent through implementation, community contribution, and the complete AI lifecycle.”

Simplicity AI SDK and Simplicity Design Intelligence Connect Intent to Product

Simplicity AI SDK has entered public Beta, giving developers and their AI coding assistants structured access to Silicon Labs SDKs, tools, documentation, and connected hardware. Rather than requiring a proprietary AI assistant, the SDK works with tools developers may already use. GitHub Copilot, Cursor, and Codex are supported in the Beta. This grounding gives general-purpose AI assistants Silicon Labs-specific context. The first officially supported experience focuses on Bluetooth® Low Energy (LE), with workflows spanning project creation and configuration, building, flashing, debugging, network and power analysis, documentation search, and hardware interaction.

Simplicity Design Intelligence extends that foundation. It is a broad and growing set of Silicon Labs capabilities designed to understand hardware and software intent, help customers realize that intent in a working product, and verify the implementation against the original intent. Hardware Intent is the first capability. It uses product requirements, board schematics, and other input hardware documentation from datasheets to meeting notes to guide pin, peripheral, and software configuration, then compares the result with the original intent. This can find pin conflicts, peripheral mismatches, and missing constraints before fabrication and help reduce avoidable board respins.

“We’ve been working closely with Silicon Labs as an Alpha customer, evaluating how the Hardware Intent Agent can streamline hardware development across our current and future products while providing feedback on new features as it progresses towards general release,” said Limor Alkelai, Co-CEO, at Risco Group. “We see its potential in enabling quicker and more robust development.”

Collaborate, Build, and Extend Through the Open-Source Community

Drawing on its experience advancing open-source development for Matter, Thread, and Zephyr, Silicon Labs is launching its open-source developer community in Beta, beginning with Bluetooth LE. The mantra is simple: build and extend. Developers can build with Silicon Labs sample applications and tooling, then extend the platform by raising issues, suggesting fixes, and contributing through pull requests.

Accepted contributions can move through the company’s normal engineering and testing processes into future SDK releases. Even before acceptance, proposed fixes and discussions can remain visible to other developers, giving the community another way to share knowledge and solve common problems. The Silicon Labs applications team will support issues raised on GitHub, and Silicon Labs plans to expand this approach to additional wireless technologies over time.

Scale the Complete Edge AI Lifecycle with Databricks

As edge AI grows, model development also needs to connect with the data and AI infrastructure enterprises already use. Silicon Labs is partnering with Databricks to bring embedded edge AI into Databricks, creating a unified, governed foundation for connecting edge devices with enterprise data, AI, and machine learning workflows.

An initial Silicon Labs MLOps SDK experience connects devices with Databricks to help capture data from the device fleet. Once the data is in Databricks, all the familiar MLOps tools and training pipelines and GPU resources are available directly for training. Once a model is trained, the Silicon Labs ML Profiler can provide directionally accurate feedback on whether a model fits target hardware and its memory and CPU requirements. That feedback can help ML engineers iterate while remaining in a familiar Databricks environment, connecting model development with the enterprise data and governance that underpin production AI. This approach helps enterprises extend AI from the cloud to the edge without creating separate data and AI stacks for embedded workloads.

A Platform that Developers Can Build and Extend

Together, these initiatives scale the development system at three levels:

The Simplicity AI SDK and Simplicity Design Intelligence help developers and their AI agents move from hardware and software intent to a working product, with Hardware Intent as the first of a growing set of Design Intelligence capabilities.The open-source community gives developers a direct way to build and extend the platform.Silicon Labs edge AI tools and Databricks connect embedded AI development with enterprise data and AI governance. Silicon Labs intends to make increasingly capable silicon easier to use and earn the position of platform of choice for embedded wireless development.

Availability and Next Steps

The Simplicity AI SDK Beta is publicly available, with official support initially focused on Bluetooth LE and support for GitHub Copilot and Codex. An alpha release of Hardware Intent, the first capability in Simplicity Design Intelligence, is planned for January 2027.

The Silicon Labs open-source community Beta launches with Bluetooth LE, and its sample applications are accessible on GitHub for code review and contributions.

Initial Silicon Labs MLOps tools are available in Databricks today.

About Silicon Labs

Silicon Labs (NASDAQ: SLAB) is the leading innovator in low-power connectivity, building embedded technology that connects devices and improves lives. Merging cutting-edge technology into the world’s most highly integrated SoCs, Silicon Labs provides device makers with the solutions, support, and ecosystems needed to create advanced edge connectivity applications. Headquartered in Austin, Texas, Silicon Labs has operations in over sixteen countries and is the trusted partner for innovative solutions in smart home, industrial IoT, and smart cities markets. Learn more at https://www.silabs.com.

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SOURCE Silicon Labs