This course, led by IBM thought leaders, provides executives and business leaders with a foundation-level understanding of AI and generative AI. You’ll get started with some key events in the history of AI. Then, you’ll learn about the importance of generative AI to businesses and get introduced to different approaches to applying AI. You will also learn about foundation models and their benefits. This course explores issues like AI hallucination, bias, and risk while also covering AI ethics, governance, and building trust. Through this course, you will gain insights into using AI to improve your service and delight your customers. Delve into the use of AI in application modernization and get best practices to gain a competitive edge.

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In this course, led by AI pioneer Andrew Ng, he shares his unique perspective on empowering you and your work with generative AI.

Ng will guide you through how generative AI works and what it can (and can’t) do. It includes hands-on exercises in which you’ll learn to use generative AI to help in day-to-day work and receive tips on effective prompt engineering, as well as learn how to go beyond prompting for more advanced uses of AI.

“Generative AI for Everyone” is for anyone who’s interested in learning about the uses, impacts, and underlying technologies of generative AI, today and in the future. It doesn’t require any coding skills or prior knowledge of AI. Business leaders will learn how generative AI can impact your business and how to develop an AI strategy to increase productivity, while professionals will get an overview of AI tools and techniques that you can apply to your work.

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AI is the most significant technological event of our time. In every industry, there will be a shuffling of winners and losers simply by how effectively each company harnesses the power of AI across the enterprise. 

Business communication is one of the biggest areas for disruption. In the US alone, gen AI could save businesses up to $1.6 trillion annually in productivity if all workers were using it for communication. But many don’t know how to move from AI experimentation to org-wide adoption.

In this webinar, you’ll hear Paul Roetzer, founder and CEO of Marketing AI Institute, share his expertise on making AI approachable and actionable for business leaders. Then Grammarly’s director of engineering joins Roetzer for a fireside chat on practical, real-world use cases and durable approaches to implementing AI across the enterprise.

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As generative AI ushers in a new era of opportunities, capabilities, and challenges, the questions on many executives’ minds are more crucial than ever: How will gen AI change your enterprise, products, and services? What are the steps to apply this technology to your business? What are competitors doing, and how can you stay ahead? 

This four-part series covers the fundamentals of generative AI, the benefits and opportunities that gen AI offers, and the risks and limitations to watch out for. Gartner experts will review some of the most popular AI-based tools, high-value use cases and first steps for implementation, and how to stay ahead of the competition with a focus on the future. Plus, you’ll be able to take away the presentation slides to leverage in conversations with your leadership team.

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Hosts Paul Roetzer, founder and CEO of Marketing AI Institute, and Mike Kaput, its chief content officer, break down all the AI news that matters and give you insights and perspectives that you can use to advance your company and your career. This podcast is here to help your business grow smarter by making AI approachable and actionable. 

Roetzer and Kaput cover a wide range of topics, offering unique perspectives on the latest AI news from around the globe and their thoughts on its effects on business, careers, and personal lives. In each show, they cover three big news stories, including AI technology developments and new features from AI platforms like OpenAI and ChatGPT, Microsoft Copilot, Google Gemini, and more. Then they break down complex and evolving AI topics, like chatbots and superintelligence, the AI agent landscape, and AI cloud wars.

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Few organizations are completely AI driven today, but a significant and growing percentage are displaying the behaviors that will get them there. What can we learn from the practices of leading-edge organizations?

Deloitte’s survey of nearly 3,000 executives explores the AI strategies and investments within their organizations. This report covers overarching AI strategy and leadership, technology and data approaches, and how leaders are helping their workforce operationalize AI.

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This year promises to bring about transformational benefits in the way we communicate and the way we work—for those who seize the opportunity. While some businesses have experimented with AI, few have unlocked its full potential. Now is the time for businesses to move toward operational excellence by harnessing the power of AI at scale to improve overall business outcomes through communicating better, not more. 

Grammarly’s annual report examines the impact that AI has had on business communication over the past year. It covers AI’s rise in the business world and the importance of investing in AI literacy to prepare your workforce to take advantage of this transformational technology.

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The data is in: 2024 is the year AI at work gets real. The use of generative AI has nearly doubled in the past six months, with 75% of global knowledge workers using it to automate content creation and streamline workflows. Employees struggling with the pace and volume of work are bringing their own AI to work. While leaders agree AI is a business imperative, many believe their organization lacks a plan and vision to go from individual impact to applying AI to drive the bottom line. The pressure to show immediate ROI is making leaders inert, even in the face of AI inevitability.

To help leaders and organizations overcome AI hesitation, Microsoft and LinkedIn looked at how AI will reshape work and the labor market broadly. The data points to insights every leader and professional needs to know—and actions they can take—regarding AI’s implications for work.

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If 2023 was the year the world discovered generative AI, 2024 is the year organizations truly began using—and deriving business value from—this new technology. In the latest McKinsey Global Survey on AI, 65% of respondents report that their organizations are regularly using gen AI, nearly double the percentage from their previous survey just 10 months ago. Respondents’ expectations for gen AI’s impact remain as high as they were last year, with three-quarters predicting that gen AI will lead to significant or disruptive change in their industries in the years ahead.

Organizations are already seeing material benefits from gen AI use, reporting both cost decreases and revenue jumps in the business units deploying the technology. The survey also provides insights into the kinds of risks presented by gen AI—most notably, inaccuracy—as well as the emerging practices of top performers to mitigate those challenges and capture value.

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Achieving AI’s full potential hinges on leaders’ willingness to lead and learn differently. This makes it possible to navigate the risks and seize the huge opportunity to reinvent work, reshape the workforce, and prepare people, responsibly. No other modern technology has impacted these areas to such a degree. However, similar to when digital came on the scene, the rush for pilots and experimentation is too often leaving robust talent strategies behind. Accenture’s research reveals an urgent need for business leaders to look beyond how AI affects specific tasks and roles and, instead, start to scale AI by redesigning processes across their organizations, and rethinking how people experience work.

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What should organizations do differently to strengthen their approach to AI transformation?

One of the most frequently cited leading practices for AI transformation is the need for a bold, enterprise-wide strategy. This critical AI project must be set and championed by an organization’s highest leadership.

This article examines how strategists are making more clear, timely, and creative choices about where to play and how to win with AI in business. It covers tips for creating an enterprise AI strategy, setting your AI vision, and making AI a competitive differentiator.

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By now, business leaders know that having a robust enterprise AI strategy is not just an option; it’s a necessity. AI offers unprecedented opportunities for innovation, efficiency, and a competitive advantage in today’s market that leaders cannot let pass. However, you’ll only realize the potential of AI if you successfully integrate it throughout your business operations. 

The journey to successful enterprise-wide AI adoption can be complex and challenging. To succeed, businesses must develop their enterprise AI strategy so that their workforce knows how to navigate the complexities of AI implementation and usage. In this blog, we’ll discuss the importance of a well-defined AI strategy and offer a roadmap for achieving enterprise-wide AI adoption.

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In the past year, usage of tools like Grammarly and ChatGPT has doubled. With that comes increased focus on the skills agenda. According to Microsoft, 82% of leaders say their employees will need new skills to be prepared for the growth of AI. That brings us to the concept of AI literacy.

This report from Datacamp breaks down the importance of AI literacy and the essential data and AI skills that leaders want to grow in their teams. It also presents the five rules for upskilling and reskilling in the era of AI. Finally, it covers why AI literacy can act as a safeguard for today’s global workforce.

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To capture the value of AI and manage risk in a sustainable way, executives need a sound, holistic, and achievable AI strategy. Building an AI strategy inclusive of generative AI requires a rigorous approach—from developing a business-driven vision to planning which initiatives to adopt and why.

This planner lays out the four key elements of any AI strategy: vision, value, adoption, and risks. Download the gen AI planning workbook to learn how to identify the strategic opportunities of generative or other AI, remove barriers to capturing AI’s value effectively, prepare to assess and mitigate a range of AI risks, and prioritize AI use cases based on business impact and feasibility.

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The integration of AI is no longer an option for businesses but a necessity. AI can help companies accelerate high-quality content production, gain new insights, scale personalized customer outreach, and enhance overall communication quality. The introduction of AI isn’t just a technological upgrade. It’s a fundamental shift in how employees communicate and how businesses operate. It’s the new language of business.

However, until everyone is empowered to “speak the same language” with AI, you’ll see only limited success. Enter AI literacy—the most important upskilling businesses need to do to gain a competitive advantage. Download this guide to learn the critical role of AI literacy, the five stages of AI adoption, the gaps holding you back from reaching the next stage, and five actionable steps to achieve enterprise-wide AI adoption.

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This article provides a general overview of responsible AI and introduces IBM’s Pillars of Trust framework. Trusted AI is a strategic and ethical imperative at IBM, but these pillars can be used by any enterprise to guide their efforts in AI.

Implementing responsible AI practices at the enterprise level involves a holistic, end-to-end approach that addresses various stages of AI development and deployment. To help leaders achieve this, IBM shares seven best practices to consider when implementing responsible AI practices.

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To help security leaders safely and ethically deploy AI, we are excited to share Grammarly’s responsible AI framework detailing our unique approach to building AI responsibly. Our hope is that the processes and principles that we have established to ensure our AI systems are safe, fair, and reliable will inspire and guide you to implement your own responsible AI practices. With these guidelines for ethical innovation, you will be better positioned to enhance the AI capabilities throughout your organization, fortify your security posture, uphold the highest ethical standards, and gain an advantage in today’s competitive market.

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We’re in the era of AI experimentation. To keep up with the rapid explosion of AI tools and usage across industries, laws and regulations are changing. It’s exciting—but it also creates uncertainty and leaves businesses vulnerable to security and compliance mishaps. As AI continues to revolutionize work, staying compliant with rapidly evolving laws and regulations is critical for IT teams and leaders alike. 

This on-demand webinar covers everything you need to know to navigate AI compliance. Tune in to hear experts explain the current AI standards impacting companies today, forecast regulations that may soon affect businesses, and help leaders prioritize their efforts based on their stage in AI adoption and deployment.

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The stakes for artificial intelligence are so high—geopolitically, economically, and societally—that governments and enterprises alike must establish a determined approach to responsible innovation and policies. Gartner predicts that by 2027, the productivity value of AI will be recognized as a primary economic indicator of national power. The level of excitement for—and fear of—AI and generative AI has sparked a growing focus on policy and regulatory work around the globe. Watch this complimentary Gartner AI webinar to hear Gartner experts take questions on the AI trends driving policymaking today and their implications for government and private sector strategic plans.

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Grammarly’s monthly newsletter is focused on promoting and advancing responsible artificial intelligence by sharing what you need to know about navigating responsible AI for your business. Our goal is to offer business leaders insights and practical guidance for navigating the complex world of AI. 

Subscribe today to get a curated list of responsible AI resources, insights from industry experts and thought leaders, and the latest industry news on AI compliance, ethics, laws, and regulations.

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Artificial intelligence teams perceive risk differently than security or compliance teams. Security teams focus on AI application attack surfaces, but with forthcoming regulations worldwide, organizations cannot overlook concerns such as data and model drift, uncontrolled bias, and privacy and cybersecurity concerns specific to AI model training and deployment. Watch this complimentary AI webinar as Gartner experts share how to best secure AI and how to implement required measures to prevent AI failures. They explore Gartner’s model operations, security, and trustworthiness (MOST) framework along with its AI trust, risk, and security management (TRiSM) model, which help to ensure that AI and security professionals can work together on the safety and security of AI systems.

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Groundbreaking. Transformative. Disruptive. Powerful. All of these words can be used to describe artificial intelligence. However, other descriptors also include puzzling, unclear, ambiguous, and risky. To get the most benefit from AI-powered technology, business leaders need to manage and mitigate the wide array of security risks it poses to their employees, customers, brand, and business as a whole. Successfully balancing the risks with the rewards of generative AI will help you manage security at the pace of innovation.

This article demystifies the key security risks of AI for businesses, provides mitigation strategies, and helps you confidently deploy secure gen AI solutions.

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The National Institute of Standards and Technology (NIST) has introduced an AI Risk Management Framework (AI RMF), intended for voluntary use and to improve the ability to incorporate trustworthiness considerations into the design, development, use, and evaluation of AI products, services, and systems.

The AI RMF is designed to equip organizations and individuals with approaches that increase the trustworthiness of AI systems and to help foster the responsible design, development, deployment, and use of AI systems over time. This framework is intended to be practical, to adapt to the AI landscape as AI technologies continue to develop, and to be operationalized by organizations in varying degrees and capacities so society can benefit from AI while also being protected from its potential harms.

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The potential of AI, especially generative AI, is immense. However, in the pursuit of progress within these new frontiers of innovation, there needs to be clear industry security standards for building and deploying this technology in a responsible manner. That’s why Google introduced its secure AI framework (SAIF), a conceptual framework for secure AI systems. SAIF is inspired by the security best practices—like reviewing, testing, and controlling the supply chain—that Google applied to software development while incorporating their understanding of cybersecurity mega-trends and risks specific to AI systems.

SAIF includes six core elements: Expand strong security foundations to the AI ecosystem; extend detection and response to bring AI into an organization’s threat universe; automate defenses to keep pace with existing and new threats; harmonize platform-level controls to ensure consistent security across the organization; adapt controls to adjust mitigations and create faster feedback loops for AI deployment; and contextualize AI system risks in surrounding business processes.

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Grammarly is both a builder and buyer of AI technology. This means we understand the nuanced challenges of researching, selecting, implementing, and adopting AI tools throughout our own enterprise—and we have helped over 70,000 teams do the same at theirs. We are proud to share our expertise and learnings in this comprehensive kit, aimed at helping IT and other buying teams make an informed purchase and ensure a safe and secure implementation of their AI solutions.

Within this enterprise AI security kit, you’ll find resources to help you through each stage of enterprise-wide AI implementation. From the 24 questions you should ask any generative AI vendor to detailed frameworks for safe and responsible AI deployment to a roadmap to navigate your team through the five stages of AI adoption, this kit has everything you need for a successful AI implementation.

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According to the G2 State of Software Report, AI writing assistants are the fastest-growing category in the AI market. View G2’s list of the best AI writing assistants and apps for businesses to cut through the noise and find the best AI assistant for your enterprise. 

AI writing assistants utilize machine learning algorithms to help users through various steps of the writing process, including research, grammar and tone checking, and localization. These tools leverage natural language processing to analyze text and provide recommendations or related content. These tools can ease the otherwise cumbersome and slow process of writing content, allowing users to write more quickly and with confidence. Augmented writing can be used by any professional looking for writing help, from content marketers trying to create more compelling material to HR representatives optimizing job listings.

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The integration of AI is no longer an option but a necessity. Those who have adopted a “wait and watch approach” are already falling behind. It’s likely that your employees are already experimenting with random, unvetted AI tools without your oversight, which puts your company’s data and your entire enterprise’s security posture at risk. As you navigate this new terrain, the challenge lies in equipping your teams with the right technology to experiment with, optimize, and then standardize generative AI usage across your entire enterprise. Only then will you reap the benefits of gen AI at scale.

On your path to gen AI adoption, you’ll need to get buy-in on your investment, have a clear picture of how you’ll use gen AI, and understand the risks and considerations for gen AI broadly and specifically to different solutions. Grammarly is breaking down everything you need to make a smart AI investment that scales with your workforce’s needs.

Download this guide to get a clear vision of how to use AI, build the best case to bring AI to your enterprise, and select the right solution that delivers on your specific needs securely.

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How do you navigate the sea of software available today to find the AI tool that’s right for your enterprise? It requires diligent up-front assessment of both the AI tool and the vendor before making an AI technology purchasing decision. Asking the right AI technology questions and getting the facts is an important but complicated task. To help you conquer it and find the right AI partner for your business, we drafted 24 questions to ask any generative AI vendor before purchasing. This article covers the topics and specific questions to ask during your evaluation.

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Where is your business on its path to achieving enterprise-wide AI adoption? Every business is starting at a different place with generative AI. Those slower to adopt likely feel behind, especially if they are still avoiding the technology altogether. Early adopters might be ahead of the curve and the competition now; however, with an emerging technology like gen AI, the curve continues to move. We are all at the beginning of a long-term shift that takes proactive planning, incremental adjusting, and the occasional pivot to achieve true transformation. The first step is identifying where your business is in its gen AI adoption journey so you can understand what’s holding you back from reaching the next stage. Take this five-minute quiz to find out where your business is—and get actionable next steps to achieve enterprise-wide AI adoption.

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Grammarly is both a user and a provider of AI, which means we understand the nuanced challenges of selecting and adopting safe and effective AI. We are proud to share our expertise and learnings in this detailed framework for choosing secure, high-quality AI partners.

Discover Grammarly’s approach to selecting an AI provider that meets your security requirements, closing a contract that gives you the benefits of AI while protecting you from vendor risk, and implementing AI across your entire organization effectively and safely.

Use this framework to ensure AI is a competitive advantage and not a business risk.

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