Summary: Generative AI is transforming how technical teams write reports, share updates, and make decisions. But as AI takes over first‑draft writing, clear human communication and strong judgment have become even more critical. This article explains why communication skills matter more than ever in AI‑enabled workplaces and introduces IEEE’s new training program designed to help professionals strengthen these capabilities.

What Is Generative AI? 

Generative artificial intelligence, also called gen AI, is a type of AI that can create new content, such as text, images, code, audio, video, or data. It relies on deep learning and neural networks to process existing data and generate new output.

How Generative AI Is Reshaping Technical Work 

In engineering and technical environments, generative AI is rapidly changing everyday workflows. Teams now rely on AI to draft documentation, prepare project updates, and outline complex reports. However, as writing shifts from manual drafting to AI-assisted creation, organizations face a new challenge: how to ensure the information you share is clear, correct, and reliable when AI writes the first draft.

Industry research highlights both the benefits and the significant skills gap surrounding the implementation of AI within the workplace.

On the other hand, the World Economic Forum revealed that 67% of business executives cite a lack of AI expertise as a major obstacle to successful adoption, with 63% identifying skills gaps as their biggest barrier to progress. As digital tools evolve, the most in-demand capabilities increasingly center on human judgement, clear communication, and thoughtful oversight. These are essential areas where AI tools cannot operate independently. 

The Hidden Risks of Basic Prompting

Relying solely on simple prompt engineering introduces vulnerabilities in technical settings. AI-generated text often includes inaccurate details, generic phrasing, unexamined assumptions, or over-automated decision logic. When technical summaries delivered to non-technical executives or partners lack proper context or nuance, the resulting miscommunication can lead to misaligned project milestones, missed deadlines, or costly operational errors.

Effective AI use requires human-centered communication strategies: 

• Understanding the audience
• Clarifying the core purpose of the message
• Actively shaping the generated output to fit the unique goals of the organization

These skills ensure that AI becomes a reliable assistant rather than a source of confusion. 

Mastering the Human Element: IEEE’s New Live Training Program

To help technical professionals navigate this evolving landscape, IEEE Educational Activities and the IEEE Professional Communication Society are offering a three-hour training session: Generative AI Communication for Technical Professionals. Attendees will walk away with different human-centered methodologies to use generative AI effectively and responsibly,  while going beyond basic prompting to focus on critical evaluation, tone adjustment, and workflow optimization. This training is designed for engineers, managers, and anyone working on cross-functional teams, where they utilize generative AI in their regular scope of work.

Hands-On Learning: Five Practical Demonstrations

The training includes five real-world demos that help participants build repeatable, human-centered communication habits:

• Audience-Aware Prompting: Learn a genre-based approach that shapes prompts around specific audiences, business goals, and organizational contexts.
• Tone, Style, and Professional Voice: Refine AI-generated text to meet professional standards and strengthen workplace relationships.
• Summarizing Technical Information: Create decision-ready summaries for executives, clients, and non-technical stakeholders.
• Cross-Cultural & Global Communication: Identify and correct hidden biases in AI-generated text for global teams.
• AI-Assisted Workflows: Build structured, reusable communication workflows that improve consistency while preserving human oversight.

Build Stronger Communications Skills for an AI-Driven Future

Whether you want to sharpen your own writing or help your entire organization adopt AI responsibly, strengthening communication skills using generative AI is key. Participants who complete the training will receive professional development credits (0.3 CEU/ 3 PDH) and a printable certificate.

To secure your spot for the training on 30 September 2026, visit the IEEE Learning Network. To learn about group options for your organization, visit the IEEE Learning Network or request details through the IEEE eLearning Portal. The training will be available on-demand via IEEE Xplore and the IEEE Learning Network (ILN).

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Summary: Continuous learning in tech is essential as AI, automation, and fast‑moving engineering fields rapidly shorten the lifespan of traditional skills. This article explains why upskilling, reskilling, and industry‑recognized digital credentials are critical for staying competitive, and how the IEEE Learning Network helps professionals build future‑ready expertise.

The technology landscape is evolving at record speed. Staying relevant requires more than just reading industry news; it demands continuous learning, upskilling, and reskilling. Fields such as artificial intelligence, semiconductor manufacturing, battery energy storage systems, and next‑generation wireless infrastructure are advancing so rapidly that the half‑life of technical skills is shrinking. For today’s engineers and technical professionals, ongoing education is the foundation of a resilient, future‑proof career.

The Push for New Skills

The data is clear. According to the World Economic Forum’s Future of Jobs Report, the global workforce is undergoing a major transformation. 85% of employers plan to upskill their teams, while 70% are actively seeking new skill sets.

With AI and automation reshaping nearly every industry, adaptability has become one of the most valuable professional traits. For technical professionals, committing to continuous learning is the most effective way to stay competitive and maintain long‑term career value.

Proving Your Expertise with Digital Credentials

Learning new skills is essential, but demonstrating them to employers is just as important. The IEEE Credentialing Program notes that many fast-growing industries face significant workforce shortages. Verified learning helps bridge that gap.

Industry-recognized digital credentials allow you to easily highlight upskilling and reskilling achievements on social media platforms and resumes. While traditional degrees remain valuable, skills-based microcredentials offer targeted, employer-trusted proof of your capabilities. They help hiring managers quickly identify your readiness for emerging roles.

Celebrating the IEEE Learning Network Anniversary

At IEEE, we want to make world-class education as accessible as the technologies you build. This July, we are celebrating the anniversary of the IEEE Learning Network (ILN).

Since its launch, ILN has been a global hub for technical education. It empowers IEEE members and tech professionals everywhere by bringing training right to their fingertips. The platform is designed specifically for the busy lives of working professionals who need reliable, high-quality resources to stay at the forefront of their fields.

Special Anniversary Offer: 10 Courses for US$10 Each

To celebrate this milestone and support your professional growth, the IEEE Learning Network is offering 10 of its most popular courses for just US$10 each, until 31 July 2026. This special offer includes:

• AI Applications in Semiconductor Packaging
• AI Standards: Best Practices for Ethical Systems
• Battery Energy Storage Systems: Design and Performance
• Battery Energy Storage Systems: Safety Considerations, Codes & Standards
• Edge AI and Nanotechnology: Transforming Healthcare, Semiconductors, and IoT
• Large Language Models: Understanding Transformer Architectures
• Navigating the AI and ML Landscape for Future Readiness
• Semiconductor Manufacturing: AI-Driven Data Collection and Preprocessing
• Semiconductor Manufacturing: Impact and Effectiveness of AI
• 5G System Principles

The future of technology is being built right now. Take charge of your career trajectory and embrace continuous learning to stay ahead of the curve, at a price designed to support your growth.

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Summary: As AI adoption accelerates, organizations need functional leaders with the skills to turn generative and agentic tools into measurable business value. Moving from productivity gains to tangible impact requires the ability to identify workflow inefficiencies, evaluate AI opportunities, lead process redesign, and align initiatives with strategic goals. These capabilities are essential for organizations seeking to transform AI investments into a long-term competitive advantage.

Across industries, organizations are investing heavily in AI tools, platforms, and talent. They hope to gain efficiency, make more informed decisions, and unlock new growth. The level of investment is significant. A recent survey of 2,400 knowledge workers and C-suite executives found that 59% of organizations invest at least US$1 million annually in AI technologies, while 97% of executives deployed AI agents during the past year.

It’s become clear that business leaders are no longer hesitant to deploy AI. However, the real question today is how to turn these deployments into measurable outcomes. To truly gain a competitive edge as these tools evolve, organizations need functional leaders who treat AI as a catalyst for transformation rather than a simple productivity booster.

Time Saved ≠ Dollars Earned

While widespread AI adoption can result in time savings per employee, it doesn’t necessarily translate into big-picture impact. A marketing manager who saves a few hours per week drafting content may become more productive, but their organization’s operating model remains unchanged. Likewise, a financial analyst could use AI to summarize reports more quickly, but this small efficiency gain does little to improve the bottom line.

Many organizations are struggling to connect the dots between their initial AI investment and true operational impact. According to McKinsey’s State of AI data survey, 64% of participants said that AI enables innovation, yet only 39% reported an impact on operating profit at the enterprise level.

Why AI Deployments Fail to Deliver

When an AI initiative doesn’t produce the promising results that were first envisioned, many blame technology by default and go straight back to the drawing board. In fact, nearly 50% of generative AI projects were abandoned last year due to poor data quality, inadequate risk controls, escalating costs, or unclear business value.

With any AI rollout, it’s vital for business leaders to remember that they’re not just solving technical gaps, but also larger organizational challenges. Many deployments fail because teams try to layer AI onto old tools instead of redesigning the workflow. Legacy processes, silos, unclear governance, and resistance to change all create significant barriers to realizing AI’s full potential.

Those who have achieved successful business outcomes with AI recognize that a deployment is an opportunity to rethink how work gets done, rather than to optimize how it currently gets done. To unlock this level of transformation, business leaders must understand how AI’s capabilities can go beyond simple automation to reimagine operations.

How Functional Business Leaders Can Lead AI Transformation

Companies frequently frame AI deployment as a project for IT teams alone. However, 53% of executives feel IT teams aren’t delivering real value with generative AI. While technology clearly plays an essential role in building and maintaining AI infrastructure, it takes a real understanding of business operations to lead transformation.

Business leaders and non-technical teams are uniquely positioned to identify how AI can add value, drawing on a deep understanding of workflows, bottlenecks, handoffs, and inefficiencies:

• Finance leaders can optimize forecasting, variance analysis, and financial planning workflows
• Supply chain leaders can leverage predictive analytics to improve inventory management, demand forecasting, and logistics 
• Customer experience teams can redesign service operations around agentic AI
• Operations leaders can identify opportunities to reduce manual work and streamline cross-functional processes

When functional leaders work together to build new frameworks, their collective expertise becomes a force for impact at the enterprise level, rather than incremental efficiency gains for individuals or a single department.

The Gap Between Business Knowledge and Technical Expertise

With countless AI tools on the market, it’s easy for organizations to keep stacking them onto their existing tech stack. But getting the most out of your investment means choosing the right tools, not more tools.

This presents a significant skills gap. Functional leaders understand their teams’ needs, yet relatively few professionals have the combination of business, analytics, and technical knowledge needed to successfully lead AI transformation at the enterprise level.

Become A Leader for AI-Driven Transformation

As AI innovation accelerates, the organizations that succeed will be those that most effectively convert capabilities into measurable results. Currently, only 20% of companies capture 74% of all AI-driven value, according to PwC’s 2026 Global AI Performance Study.

This presents a major opportunity for leaders who can:

• Identify value leakage
• Redesign workflows
• Lead organizational change
• Align AI initiatives with measurable business goals

The IEEE | Rutgers Online Mini-MBA: Artificial Intelligence is designed to empower non-technical business professionals with the expertise needed to translate AI capabilities into measurable outcomes. Over 12 weeks, participants gain a practical understanding of AI, its impact on core business functions and the knowledge to evaluate, implement and scale AI initiatives across their organization.

The curriculum combines strategic frameworks with real-world applications. As a result, learners develop the skills to identify opportunities, collaborate with technical teams, and build a roadmap for AI-driven transformation. The program equips leaders to move beyond experimentation and turn AI investments into a competitive advantage.

Discover how you can enroll as an individual or connect with a dedicated IEEE content specialist to enroll your employees in the upcoming September cohort. Learn more and take the next step before the 11 September enrollment deadline.

More Upskilling Opportunities from IEEE

Advance your career with the IEEE | Rutgers Mini-MBA for Engineers and Technical Professionals. This unique program bridges the gap between business and engineering, helping technical professionals grow in their careers. Learn from top experts and enjoy a flexible, self-paced format. IEEE is proud to partner with Rutgers University and UnitelmaSapienza for a special session in November 2026 focused on targeted training for students and professionals. Learn more today!

 

Summary: The IEEE Credentialing Program provides globally recognized digital credentials that help organizations validate technical skills, accelerate workforce development, and build reliable talent pipelines in fast‑growing fields like AI and semiconductor manufacturing. Learners also benefit from stackable, skills‑based microcredentials that support continuous career advancement.

In today’s rapidly evolving technology landscape, industries such as artificial intelligence, semiconductor manufacturing, and advanced engineering are growing faster than traditional workforce pipelines can support. As a result, employers are moving away from degree‑only hiring models and embracing skills‑based validation, where demonstrated competency is the new currency of the labor market.

To stay competitive, organizations are investing in continuous learning programs that upskill existing staff, speed up onboarding, and build reliable talent pipelines for emerging technical roles.

To meet these needs, the IEEE Credentialing Program issues validated digital credentials for professional development and skills assessment on behalf of education and training providers around the world. 

Two Credential Pathways for Professional Validation

The IEEE Credentialing Program offers two types of digital credentials. In both cases, learners receive verifiable, shareable digital badges stored in a secure digital wallet. 

1. Professional Certificates

These credentials validate the successful completion of educational courses, training programs, conferences, or events. Many provide Professional Development Hours (PDH) or Continuing Education Units (CEU), essential for maintaining professional engineering licenses and demonstrating ongoing technical growth.

2. Skills-Based Microcredentials

Built on a competency‑based model, these microcredentials require learners to demonstrate specific, real‑world skills through assessment. They are:

• Agile: rapidly developed and deployed
• Stackable: enabling progressive skill-building
• Industry-Aligned: focused on practical, job‑ready competencies

Key Benefits for Industry and Learners

The IEEE Credentialing Program serves as a global “gold standard” for technical validation, offering strategic advantages for workforce developers, employers, and learners.

Global Recognition

Credentials are trusted in 190+ countries, backed by the reputation of the world’s largest technical professional organization.

Agility and Speed

Skills can be demonstrated through:

• Simulations
• Work-based learning
• Hands-on assessments

This enables workers to gain expertise faster than traditional academic cycles.

Increased Accessibility

Microcredentials reduce time and financial barriers, allowing learners to:

• Build skills incrementally
• Earn credentials as they progress
• Share achievements instantly across platforms

Validated Talent Pipelines

Employers gain confidence that technicians and engineers possess the exact competencies required for high‑growth sectors such as AI, semiconductors, robotics, and clean energy.

Getting Started with IEEE Credentialing

With more than 30 years of experience in training validation, IEEE partners with industry, academia, and workforce development organizations to meet the demands of a rapidly changing labor market. By providing a scalable, globally recognized way to verify technical skills, the IEEE Credentialing Program empowers educators and employers to keep pace with modern workforce needs.

Learn more about the IEEE Credentialing Program.

Summary: IEEE Education Week 2026 offers a global lineup of courses, webinars, and resources to help professionals, students, and educators build in‑demand technical skills. As emerging fields like AI, quantum networking, and sustainable engineering accelerate, this weeklong event provides essential opportunities for upskilling and staying competitive in a rapidly evolving tech landscape.

The tech landscape is evolving faster than ever. According to the 2026 Tech Talent Outlook, the demand for specialized skills in generative AI architecture, quantum networking, and sustainable engineering has reached an all-time high. Today, a staggering 91% of tech professionals report that continuous upskilling is essential to stay competitive in an increasingly automated workforce.

With the market rewarding professionals who can bridge legacy systems and emerging intelligence, now is the ideal time to invest in your growth. IEEE Education Week 2026 helps you strengthen your skills and stay ahead of evolving technologies.

Join the Global Celebration: 11–19 April 2026

IEEE Education Week (11-19 April 2026) is a weeklong celebration of learning opportunities provided by the world’s largest, technical, professional association and its global network of Societies and Councils.

Explore a curated ecosystem of courses, webinars, events, and educational resources designed to help IEEE Volunteers, students, STEM educators, and technical professionals lead the next wave of innovation.

What Does IEEE Education Week Offer?

Whether you are looking to master a new programming paradigm or understand the ethics of autonomous systems, this week offers a wealth of resources:

• Exclusive Webinars and Hybrid Events: Deep‑dive sessions on topics such as Inspiring Tomorrow’s Innovators, How to Be a CTO, and Mastering the Modern Job Market.
• Educational Courses and Learning Resources: Short, impactful courses that help you build in‑demand skills and verify your expertise with employers.
• Special Discounts and Offers:Save on IEEE courses, Society memberships, publications, and more. You’ll also find special opportunities related to scholarships, calls for proposals, competitions, and student programs.

Who Can Participate?

IEEE Education Week is open to anyone committed to the pursuit of technical excellence, including:

• Professionals working in the technical field
• University students and faculty members
• Pre-university STEM enthusiasts and educators

You do not need to be an IEEE member to participate in many of these events. However, IEEE members receive exclusive discounts on a variety of offerings such as conferences, courses, publications, and more. If you’re not yet a member, this is the ideal week to join and unlock your professional potential. Click here to join IEEE.

Represent an IEEE-Affiliated Group?

There’s still time to participate. If your IEEE Society, Council, Region or Section is hosting an educational event or launching a new learning opportunity, make sure it’s featured on the official IEEE Education Week portal by submitting event details. We want to amplify your impact!

Save on eLearning

Celebrate IEEE Education Week with an exclusive 25% discount on some of the most popular course programs on the IEEE Learning Network! Use code ILNIEW26. Offer valid until 30 April 2026.

Learn How to Get Involved. See you at IEEE Education Week 2026!

Summary: Technical writing is a critical skill for engineers and technical professionals who want to advance their careers and ensure their work has real impact. Clear, structured communication helps engineers document processes, explain research, influence decisions, and meet the expectations of scientific audiences.

In fast‑moving technical fields, we devote countless hours to mastering new tools, frameworks, and methodologies. Yet one of the most critical skills for career advancement often receives far less attention: technical writing.

Whether you are an engineer, researcher, or subject matter expert, your ability to communicate clearly is just as important as your technical expertise. Without strong writing, your insights, data, and innovations may never reach the colleagues, stakeholders, and journals that need them.

The Professional Cost of Poor Communication

Writing is often mislabeled as a “soft skill,” but in engineering and scientific environments, it is a core professional competency. Clear communication enables you to:

• Influence decision-makers.
• Document processes and methodologies
• Justify budgets and resource needs
• Explain research findings

When writing is unclear, overly complex, or poorly structured, the value of your work becomes harder to recognize. A project proposal may be overlooked, a research paper may be rejected, or a technical recommendation may be misunderstood. Clarity is not optional; it is essential for professional impact.

The Structure of Technical Authority

Technical writing differs from other forms of communication because it relies on logic, structure, and predictability. Readers in scientific and technical fields expect information to follow established patterns. When writing deviates from these expectations, comprehension suffers.

One of the most widely used frameworks is the IMRaD structure, common in scientific and technical publications:

• Introduction: What problem are you addressing?
• Methods: How did you study or approach the problem?
• Results: What did you find?
• Discussion/Conclusions: What do the findings mean for the field?

Mastering IMRaD not only strengthens your writing, it allows you to present your work in a way that aligns with the professional standards of organizations like IEEE.

From Research to Publication: Elevating Your Technical Writing

Recognizing the importance of strong writing is the first step. The second is developing a systematic approach to the writing process. To support professionals in this journey, IEEE offers a comprehensive program: From Research to Publication: A Step-by-Step Guide to Technical Writing.

Developed in collaboration with the IEEE Professional Communication Society, this course is designed for those who must produce technical journal articles, reports, or research papers, especially those without formal training in technical communication.

Course Program Overview

This course provides deep overviews of the traditional formats and expectations of scientific articles. Participants receive practical tools to sharpen their skills, including strategies for using Generative AI effectively within the writing workflow.

What You Will Learn	Why it Matters
IMRaD Pattern	Ensures your paper follows standard scientific expectations.
Editing Techniques	Improves clarity and reduces technical jargon.
Authorship Issues	Navigates the complexities of team-based research.
Publishing Strategy	Helps you identify the right journals for your work.

Who Should Attend

This program is specifically designed for:

• Graduate and undergraduate students writing their first academic articles
• Early career professionals looking to establish a publication record
• Subject matter experts who need a refresher on formal reporting

The course is taught by Dr. Traci Nathans-Kelly, Director of the Engineering Communications Program at Cornell University. With over 30 years of experience, Dr. Nathans-Kelly specializes in helping technical experts become impactful contributors. She is a prominent figure within IEEE, serving on the Board of Governors for the Professional Communication Society and as an editor for the IEEE Professional Engineering Communication book series.

Invest in Your Professional Voice

Your technical skills may solve complex problems, but your writing skills ensure those solutions are understood, adopted, and recognized. By strengthening your ability to write for a technical audience, you amplify the reach and impact of your work.

For Individuals

Interested in access for yourself? Visit the IEEE Learning Network (ILN) to explore the From Research to Publication: A Step-by-Step Guide to Technical Writing course. Participants earn professional development credit and a shareable digital badge. IEEE members save US$100.

For Organizations

Connect with an IEEE Content Specialist today to learn how to get access to this program for your organization.

Summary:  Discover the top tech trends of 2025 — from AI in semiconductors to battery storage. Explore new IEEE Learning Network courses that help you prepare for 2026.

A Year of Rapid Change

As 2025 comes to a close, the pace of innovation has accelerated across every major industry. AI reshaped semiconductor manufacturing. Battery storage technologies advanced faster than expected. Power systems grew more intelligent and resilient. And large language models continued to redefine how engineers design, test, and communicate.

These shifts aren’t isolated events. Instead, they point directly to what professionals will need to understand in 2026. By tracking these trends now, you can apply the latest engineering practices with confidence. This way, you can stay competitive in a fast‑moving landscape.

Below, you’ll find the most influential tech trends of 2025 — each paired with a new IEEE Learning Network course developed by IEEE Educational Activities and partners across IEEE. These are designed to help you build the skills that matter most for the year ahead.

AI Applications in Semiconductor Packaging

Semiconductor packaging plays a critical role in device reliability and performance. In 2025, AI began transforming packaging workflows by improving failure prediction, lifecycle modeling, and performance analysis. These tools now deliver insights that traditional methods simply can’t match. 

Why it matters: AI-enabled packaging boosts reliability. As devices become smaller and more complex, packaging challenges grow. AI helps engineers solve these challenges with greater speed and precision, strengthening both product quality and supply chain resilience.

AI Applications in Semiconductor Packaging: Developed in partnership with the IEEE Electronic Packaging Society, this course shows how AI enhances packaging reliability. Learners will compare traditional approaches with advanced predictive techniques. They will explore performance modeling and failure analysis. Learners will also learn how AI improves quality assurance and manufacturing efficiency.

Mastering AI Integration in Semiconductor Manufacturing

Beyond packaging, AI is reshaping semiconductor production from end to end. In 2025, factories expanded their use of AI-driven systems that combine IoT sensors, edge computing, and predictive analytics. These tools now monitor processes in real time and help engineers optimize production faster than ever. 

Why it matters: AI scales manufacturing intelligence. When every stage of production becomes smarter, manufacturers reduce defects, improve yield, and accelerate innovation. This shift is essential for staying competitive in a global market.

Mastering AI Integration in Semiconductor Manufacturing: Developed in partnership with the IEEE Computer Society, this program provides a comprehensive roadmap for engineers and professionals. It covers AI fundamentals, data handling, and advanced techniques for integrating AI into semiconductor manufacturing. Learners explore case studies on process optimization, production efficiency, and quality assurance. They gain practical insights into how IoT sensors and edge computing can transform manufacturing environments. By the end, participants will be equipped with the skills to design and implement AI‑driven solutions. This enhances productivity and reliability in semiconductor production.

AI for Power and Energy Systems: Applications, Challenges, and Opportunities

Power systems grew more complex in 2025 as renewable energy, distributed generation, and smart grid technologies expanded worldwide. AI, especially convolutional neural networks (CNNs), helped solve challenges such as power flow analysis, fault detection, and grid stability.

Why it matters: AI strengthens grid resilience. Smarter power systems support sustainability goals while protecting communities from disruptions.

AI for Power and Energy Systems: Applications, Challenges, and Opportunities: Developed with the IEEE Power & Energy Society, this course explores how AI techniques can be applied to real‑world power system problems. Learners gain exposure to case studies, security challenges, and opportunities for grid modernization. They examine how AI can optimize performance, improve reliability, and support the transition to cleaner energy. 

Battery Energy Storage Technologies and Applications

Energy storage became even more essential in 2025. Advances in battery chemistry, safety standards, and sector‑specific applications accelerated adoption across transportation, utilities, and industrial systems.

Why it matters: Storage drives sustainability. Batteries enable consistent, reliable energy from renewable sources like solar and wind. As electrification expands, storage becomes the backbone of resilient, low‑carbon infrastructure.

Battery Energy Storage Technologies and Applications: Created with the IEEE Power & Energy Society, this program provides a deep dive into the fundamentals of battery chemistry and design. It explores applications across sectors such as transportation and grid integration. Furthermore, it examines technical considerations including safety standards, lifecycle management, and advanced developments in next‑generation storage systems. Learners gain practical insights into how battery technologies are shaping the future of sustainable energy. They also learn how to apply these concepts to real‑world engineering challenges.

From Research to Publication: Technical Writing for Engineers

Scientific breakthroughs only have impact when they’re communicated clearly. In 2025, the rise of Generative AI and increasingly complex research made strong technical writing skills more important than ever. Engineers must understand the conventions of scientific publishing to ensure their work is understood, cited, and applied.

Why it matters: Clear writing amplifies impact. Strong communication turns ideas into knowledge that shapes industries and advances society.

From Research to Publication: A Step‑by‑Step Guide to Technical Writing: Developed with the IEEE Professional Communication Society, introduces the methods and traditions of writing technical and scientific articles. It focuses on formats used in IEEE journals. Learners gain practical guidance, supplemental materials to refine their skills, and insights into leveraging Generative AI effectively in the writing process.

Large Language Models: Understanding Transformer Architectures

Transformers remained the foundation of modern AI in 2025. Engineers needed to understand not only how transformers work, but also why their design — including self‑attention, multi‑head attention, positional encoding, and residual connections — enables massive scalability.

Why it matters: Transformers are the core of today’s AI systems. Mastering them prepares professionals to design, evaluate, and deploy advanced models responsibly.

Large Language Models: Understanding Transformer Architectures: A deep dive course into the original transformer model. It was developed in partnership with the IEEE Computer Society. Learners explore each core component of the architecture and examine how transformers overcame the limitations of recurrent neural networks (RNNs). They gain insight into how these innovations enable today’s large‑scale language models.

Large Language Models: Evolution, Impact, and Hands‑On Exercises

Language models evolved rapidly in 2025, moving from statistical methods to advanced transformer‑based systems like LLaMA 3. Engineers now need both theoretical understanding and practical skills to apply these models responsibly.

Why it matters: Practical LLM skills drive real‑world impact. Understanding model evolution, optimization, and risk mitigation helps professionals use AI effectively and ethically.

Large Language Models: Evolution, Impact, and Hands‑On Exercises: Developed in partnership with the IEEE Computer Society, this course traces the progression of language models from statistical approaches to modern transformer architectures. Learners explore milestones in AI development and examine real‑world applications. They also gain practical experience through a hands‑on gradient descent exercise on model optimization. By combining historical context with applied practice, the course equips participants to understand both the opportunities and challenges of deploying LLMs in engineering and technology.

Looking Ahead to 2026

The trends of 2025 laid the foundation for what comes next. In 2026, expect deeper AI integration in manufacturing, wider adoption of battery storage, and continued advances in power systems and language models. By investing in your skills today, you position yourself to lead tomorrow’s innovations.

Summary: Artificial intelligence is reshaping industries, yet a persistent AI skills gap limits workforce readiness. IEEE’s AI training and professional development programs bridge this divide, empowering employees and organizations to harness AI for innovation, efficiency, and growth.

AI isn’t just transforming technology, it’s revolutionizing how we work, innovate, and compete in the global marketplace. Yet despite AI’s growing prominence, a significant AI skills gap persists across industries. Many professionals and organizations are left struggling to harness AI’s full potential through effective AI education and professional development.

The AI Adoption Paradox in Professional Development

Recent research highlights a striking disconnect: while technology leaders identify AI as the most critical technology for 2025, most employees remain unclear on how to integrate AI tools into daily workflows. This gap represents both a challenge and an unprecedented opportunity for organizations seeking comprehensive AI training solutions.

IEEE’s global study, The Impact of Technology in 2025 and Beyond, surveyed 350 technology leaders—including CIOs, CTOs, and IT directors—and paints a compelling picture of AI’s strategic importance for workforce development. More than half ranked AI technologies, encompassing predictive and generative AI, machine learning, and natural language processing, as their top priority entering 2025.

The enthusiasm is backed by action: 

• 20% of respondents regularly use generative AI in business applications, citing tangible operational value
• 24% acknowledge AI’s benefits and plan to explore practical applications through structured AI education programs
• 30% have high expectations and intend to experiment with smaller-scale AI training initiatives

Yet, this executive-level confidence doesn’t translate to the broader workforce.

This disconnect creates a critical bottleneck: organizations eager to embrace AI transformation but lacking the skilled workforce to execute their vision.

The Strategic Imperative for AI Education and Skills Development

The stakes couldn’t be higher for professional AI training. Organizations that strategically deploy AI through professional training are positioned to significantly outperform competitors in growth, efficiency, and innovation.

Effective AI implementation enables companies to:

• Make informed, data-driven decisions
• Optimize resource allocation
• Deliver personalized customer experiences
• Streamline project management

Business leaders who understand AI’s capabilities and limitations through structured AI training will be better equipped to navigate the competitive landscape ahead.

However, the question isn’t whether to invest in AI education and professional development, it’s how to do it effectively and at scale through proven AI training programs.

IEEE AI Training and Professional Development

To address this critical skills gap, IEEE Educational Activities has developed a robust AI education ecosystem that bridges the divide between AI’s potential and practical implementation. These targeted AI training courses ensure employees gain both cutting-edge knowledge and hands-on skills to drive innovation.

Each course provides:

• Professional development credits (PDHs and CEUs)
• Shareable digital badges to showcase verified AI proficiency

Featured AI Training Programs

• Artificial Intelligence and Machine Learning in Chip Design is a four-hour intensive AI training covering design automation applications, deployment strategies, and future design trends. Created in partnership with IEEE Future Directions, this AI education course addresses the semiconductor industry’s growing need for AI-enhanced design processes.
• Integrating Edge AI and Advanced Nanotechnology in Semiconductor Applications explores the convergence of AI, edge computing, and nanotechnology over five comprehensive hours of AI training. Developed with the IEEE Computer Society, this professional development program addresses the critical intersection where hardware meets intelligent software.
• Mastering AI Integration in Semiconductor Manufacturing provides five hours of deep-dive AI education content on how artificial intelligence enhances production efficiency, optimizes manufacturing processes, and improves product quality. This IEEE Computer Society partnership addresses one of industry’s most pressing AI training and modernization challenges.
• AI Applications in Semiconductor Packaging delivers two hours of specialized training content on how artificial intelligence revolutionizes packaging reliability, performance prediction, and failure analysis in semiconductor manufacturing. This IEEE Electronic Packaging Society partnership addresses critical industry needs for advanced AI methodologies in packaging optimization and lifecycle management.

Advanced AI Training for Leaders

For organizations and individuals seeking comprehensive AI leadership development, IEEE has partnered with Rutgers University to launch the IEEE | Rutgers Online Mini-MBA: Artificial Intelligence program. This intensive AI education offering goes beyond technical training to address strategic AI implementation, helping participants understand how to leverage artificial intelligence for specific industries and job functions.

The mini-MBA program equips learners with advanced AI training to strategically address business challenges, optimize processes, maximize data effectiveness, enhance customer service, and drive overall organizational success through AI education. With both individual access and company-specific cohorts available, organizations can customize AI training experiences to meet their unique professional development needs.

Driving Innovation Through AI Skills Development

Whether you’re an experienced professional expanding your AI expertise or an organization looking to transform workforce capabilities, IEEE’s AI training programs provide the foundation for sustained innovation and growth.

Learn more about IEEE’s corporate solutions and professional development opportunities in artificial intelligence.

Microcredentials offer learners an accessible and affordable way to gain and market industry-recognized technical skills that provide pathways into new opportunities. 

Emerging technologies like blockchain, artificial intelligence, and robotics are creating a global demand for skilled technicians to fill critical roles. While many of these positions require specific skills, they don’t always demand a two or four-year degree. This is where skills-based microcredentials come in.

Microcredentials are a relatively new type of credential that represent the mastery of specific skills in a learning program. In order to earn them, learners must demonstrate the skill through a skills validation assessment. They can be “stacked” to show a growing skillset in a defined area, allowing learners to earn several microcredentials in one program. Microcredentials are also verifiable and digitally shareable, highlighting the skills learners have acquired for potential employers. 

Providing new pathways into technical careers 

It’s important to understand where skills-based microcredentials fall in the wider scope of credentials earned through learning programs. Microcredentials remove barriers to entry in technical fields by offering a more accessible path for learners compared to traditional degrees, as they require less time and financial investment. They allow aspiring technical professionals to quickly gain and demonstrate the specific knowledge, skills, and abilities needed to secure entry-level opportunities. Additionally, microcredentials provide paths for advancement by enabling working professionals to upskill their current abilities or reskill into new areas.

Skills-based microcredentials provide new pathways into technical careers in three ways: 

1. Skilling: Pathways to entry-level opportunities  

Microcredentials can help new workers build and demonstrate the knowledge, skills, and abilities needed for technical entry-level positions. Unlike broader two- or four-year degrees, microcredentials focus on the specific competencies of the role, significantly reducing the time and cost for a learner to become job-ready. 

2. Upskilling: Pathways to advanced opportunities 

For current technical professionals, microcredentials enable continuous professional development by allowing learners to quickly upskill, or acquire new, specialized skills to meet an organization’s needs or new career opportunities. 

3. Reskilling: Pathways to Emerging Industry Careers  

As technology evolves, certain jobs may change or even become obsolete while new ones emerge. Microcredentials offer a swift and agile pathway for career transition, enabling professionals to proactively reskill for evolving business needs or opportunities in emerging technical fields.

Getting Started 

More universities and training organizations are starting to offer microcredentials because of the value they provide for learners and industry, but their quality and definitions can vary. This makes it challenging for students to understand the true value of the microcredential. 

With over 30 years of experience, IEEE has the credibility and infrastructure to offer trusted verification of skills-based microcredentials. We partner with industry leaders, training providers, and conference organizers to validate training programs and issue verified professional credentials that meet rigorous industry standards.

Newest eLearning offering Credentials

In addition to skills-based microcredentials, IEEE Educational Activities is offering a variety of new online courses. When you successfully complete courses offered by IEEE Educational Activities, you’ll earn continuing education credits that can be used towards maintaining your Professional Engineer license. Plus, you can also earn digital badges from course programs to display on your LinkedIn profile, highlighting your commitment for professional growth to potential employers.

AI and Chip Technology

• AI Applications in Semiconductor Packaging:
  Explore how AI is transforming semiconductor packaging reliability, contrasting traditional methods with advanced techniques for performance prediction, failure analysis, and lifecycle optimization.
• Artificial Intelligence and Machine Learning in Chip Design:
  In this program, learners will gain comprehensive knowledge of AI and machine learning applications in chip design and EDA tools, exploring high-value use cases, relevant technologies, and implementation strategies to improve product quality and design efficiency. Learners will also understand how these advances are fundamentally transforming chip design methodologies and prepare for future developments in the field.
• Integrating Edge AI and Advanced Nanotechnology in Semiconductor Applications:
  This course series explores the intersection of AI, edge computing, and nanotechnology through five connected courses. Learners will cover foundational concepts, nanomagnetic logic, semiconductor innovations, real-world applications, and future system architecture, gaining comprehensive skills in Edge AI Nanoinformatics for modern computing environments.
• Mastering AI Integration in Semiconductor Manufacturing:
  In this course, learners will explore how AI is revolutionizing semiconductor manufacturing by examining fundamental AI integration concepts, data collection techniques, process optimization methods, and supply chain applications. Participants will gain practical skills to implement AI strategies that enhance production efficiency, improve product quality, and make data-driven decisions within their organizations.

Technology and Infrastructure

• Battery Energy Storage Technologies and Applications:
  This comprehensive program offers an in-depth exploration of battery storage technologies, covering fundamental concepts, applications across various sectors, technical design, safety regulations, and advanced developments in transportation applications.
• IEEE 802.11ax: An Overview of High-Efficiency Wi-Fi (Wi-Fi 6):
  This course explores IEEE 802.11ax (Wi-Fi 6) technology, covering PHY layer innovations (day one) and MAC layer advancements (day two). Learners will examine how 802.11ax achieves higher efficiency and improved performance in dense wireless environments through better spectrum utilization, flexible multi-access schemes, and enhanced interference management.

Data and Digital Strategy

• Machine Learning: Predictive Analysis for Business Decisions:
  In this course, learners will gain an overview of machine learning types and applications for enterprise data analysis, while mastering the technical vocabulary and high-level concepts needed to effectively deploy machine learning solutions in business operations.
• Protecting Privacy in the Digital Age:
  In this course, learners will gain a comprehensive understanding of digital privacy, including how to operationalize privacy in organizations, engineer privacy into systems, make privacy usable for end users, and address emerging technological challenges to privacy. This program addresses the critical need for privacy protection in our increasingly digitized world where technological innovations pose growing risks to personal information security.

Check out more eLearning Courses that offer digital credentials on the IEEE Learning Network. 

Read more about different types of credentials and how they can advance your career here.

September brings two powerful reminders of the value of continuous learning and the people who make it possible: Online Learning Day (September 15) and IT Professionals Day (September 16).

While these observances originated in the U.S., their impact is universal. In today’s digital-first world, accessible learning and skilled technical professionals are essential everywhere, and IEEE is proud to support that mission.

Why Online Learning Matters—Now More Than Ever

Online learning day celebrates how digital education breaks down barriers and expands access to knowledge. For engineers and technical professionals, it’s a reminder that learning is a lifelong journey—not a one-time event.

Online learning has transformed how professionals grow and adapt. It’s no longer a luxury—it’s a necessity. The global online education market is projected to reach $203.81 billion by the end of 2025, with over 1.12 billion users expected worldwide by 2029.

Honoring IT Professionals: The Backbone of Innovation

IT Professionals Day recognizes the individuals who keep our digital infrastructure secure, efficient, and resilient. These professionals are essential to every industry, and their expertise drives innovation across borders.

According to forecasts from the U.S. Bureau of Labor Statistics, the U.S. tech workforce is projected to grow at twice the rate of the overall labor market over the next decade. This signals a powerful opportunity for IT and other technology professionals!

IEEE supports IT professionals globally through courses that address real-world challenges, from automotive cybersecurity to privacy protection in the digital age. ILN’s content is designed to meet the evolving needs of this critical workforce, wherever they are.

IEEE Learning Network: Online Courses for Engineers and Technical professionals

The IEEE Learning Network (ILN) is a trusted destination for engineers, technologists, and professionals seeking to upskill, stay ahead of emerging trends, and grow their careers. With hundreds of expert-led courses available on demand, ILN offers flexible, high-quality learning tailored to a global audience.

Why Choose ILN?

• Learn directly from IEEE subject matter experts
• Earn CEUs and PDHs for professional development
• Explore trending topics like AI, cybersecurity, smart grid standards, and more
• Access content anytime, anywhere – on your schedule

Celebrate with 25% Off Online Courses

In celebration of Online Learning Day and IT Professionals Day, IEEE is offering 25% off a curated selection of online courses designed to elevate your skills and expand your expertise.

From AI ethics to distributed energy resources, these courses are built for today’s technical professionals, no matter where they live or work.

Take 25% off select courses from 12–20 September using promo code ILN25 at checkout. Offer ends 20 September at 11:59 PM ET.

Featured course programs include:

• All About IOT Security
• AI Standards: Roadmap for Ethical and Responsible Digital Environments
• Artificial Intelligence and Ethics in Design
• Automotive Cyber Security: Protecting the Vehicular Network
• IEEE Software and Systems Engineering Standards Used in Aerospace and Defense
• Integrating Edge AI and Advanced Nanotechnology in Semiconductor Applications
• Introduction to IEEE Std 1547-2018: Connecting Distributed Energy Resources
• Machine Learning: Predictive Analysis for Business Decisions
• NESC® 2023: National Electrical Safety Code
• Protecting Privacy in the Digital Age

Explore the full catalog at IEEE Learning Network and start your learning journey today.

Join us in celebrating lifelong learning and the professionals who power innovation around the world.