grammarlyAug 13, 2026

Grammarly Authorship Is Now Available in Blackboard (opens in new tab)

Grammarly Authorship aims to make student writing transparent as AI becomes common in education. It tracks whether text was typed by a student, generated by AI, copied, or rephrased, allowing students to demonstrate their process and instructors to evaluate work with more confidence. Its new Blackboard integration brings these reports directly into assignment workflows, building on integrations with Google Docs, Microsoft Word, Word Online, Grammarly Docs, and Canvas. ## The Purpose of Grammarly Authorship - Authorship addresses concerns shared by instructors and students: - Instructors need confidence that submitted work is authentic. - Students need credit for their own contributions and protection from false accusations. - It emphasizes transparency and attribution rather than relying solely on AI detection. - Students retain control over viewing and sharing their writing-process data, while reports cannot be altered before submission. - The system recognizes: - Human-typed text - AI-generated content pasted into a document - AI-generated content created within a document - Copied text - Text rewritten with Grammarly’s generative AI ## Adoption and Reported Results - Authorship launched in Google Docs beta in October 2024 and later expanded to Grammarly Docs, Microsoft Word, and Word Online. - Students have created more than 5 million Authorship reports. - Rowan-Cabarrus Community College reported a reduction in academic-integrity violations from 27 to 1 semester-over-semester after adopting Authorship across its English department. ## Blackboard Integration Workflow - Instructors enable **Enable Grammarly Authorship** in the Originality Report section when creating a Blackboard assignment. - Students continue writing in their preferred tools and activate Authorship tracking. - Authorship automatically records the sources and origins of text. - Students generate a shareable report link and set its access to **Anyone with the link**. - They submit the link alongside their assignment through Blackboard’s normal submission process. - Instructors receive a class-level overview and can inspect an individual student’s full writing-process replay when necessary. - This allows instructors to focus attention on unusual cases instead of manually investigating every submission. ## Benefits for Students, Instructors, and Institutions - **Students** - Can demonstrate their writing process with minimal additional effort. - Receive recognition for their own thinking, whether or not they used AI. - Build responsible AI-literacy and source-attribution habits. - **Instructors** - Can require Authorship reports at the assignment level. - Review reports from a centralized Blackboard view. - Spend less time investigating and more time using writing-process evidence for instruction. - **Institutions** - Gain a scalable academic-integrity approach across departments. - Use existing writing and learning-management tools rather than requiring major workflow changes. - Establish a consistent institutional response to AI use. Grammarly Authorship’s Blackboard integration is available to Grammarly for Education customers with institution-wide plans that use Blackboard. It offers a practical way to make AI-era writing more accountable by combining student consent, process evidence, and existing assignment workflows.

gen-aigrammarlygoogle-docsacademic-integrity+4

grammarlyJun 15, 2026

Say It, Then Send It with Speech to Text (opens in new tab)

Writing on a phone remains difficult because typing is slow and native dictation produces messy transcripts. Grammarly Keyboard’s speech-to-text feature aims to solve this by converting natural speech into polished, send-ready text directly within any iOS app. It removes filler words, verbal corrections, and grammar errors while preserving the speaker’s tone and intent. ## Polished Dictation Anywhere - Speech-to-text is built into the Grammarly Keyboard. - Users tap the microphone, speak naturally, and receive cleaned-up text in the active app. - The feature supports multiple languages, accents, and speaking styles. - Users can switch between dictation and typing or further edit text with Grammarly’s keyboard. - Grammarly’s AI assistant is also available within the same keyboard. ## Designed for Mobile Writing - The feature targets frequent mobile writers, including professionals, students, and people capturing ideas while away from a desk. - Noise reduction helps improve recording quality. - Recording starts only when the user taps the microphone. - An on-keyboard indicator and iOS’s orange status light show when the microphone is active. - Audio is deleted after transcription and is not stored, linked to the user’s account, or used for model training. ## How to Get Started - Download Grammarly for iOS from the App Store. - Add Grammarly under **Settings → General → Keyboard → Keyboards → Add New Keyboard**. - Enable full access so the keyboard can operate across apps. - Open any text field, tap the Grammarly microphone, and begin speaking. Grammarly’s speech-to-text is presented as a practical alternative to raw phone dictation, especially for users who want fast, polished mobile messages without manual cleanup.

aiiosspeech-to-textmobile-keyboard+2

grammarlyMay 29, 2026

A University of Florida Professor Stopped Fighting AI in His Classroom: A Peer-Reviewed Study Followed (opens in new tab)

Dr. Brian Harfe addressed generative AI in student writing by redesigning an essay assignment instead of relying on surveillance or AI detectors. In a 310-essay study, students began with AI-generated drafts and revised them into essays reflecting their own views, with word-level provenance tracked through Grammarly Authorship. The results suggest that assignment design can encourage meaningful engagement and provide more reliable insight into AI use than surveys or detection scores. ## Limits of Surveys and AI Detectors - Surveys are influenced by students’ perceptions of acceptable behavior, fear of penalties, and difficulty recalling how much AI assistance they used. - AI detectors provide probabilistic judgments rather than proof. - Most detectors assess an entire document and cannot identify which passages were AI-generated or how the text developed. - These methods measure the final product, not the writing process. ## An Assignment Built Around AI - In the University of Florida course “Can We Design Better Humans? Should We?”, students had to start with a fully AI-generated essay. - They then revised it to express their own views on human cloning and genetic engineering. - Students could keep, modify, or discard as much of the AI draft as they wanted. - Because AI use was explicitly permitted, the assignment removed the incentive to conceal it. - Grammarly Authorship tracked whether each word was typed by the student, copied from AI, or drawn from another source. - Students submitted authorship reports, allowing Harfe to replay the evolution from AI draft to final essay. ## Findings from 310 Essays - The study included students from seven colleges and more than 100 majors. - Students who wrote more original text generally spent more time completing the assignment, linking time-on-task with deeper revision. - STEM students produced more human-generated text than non-STEM students, although both groups were similarly likely to agree with the AI draft. - Higher-performing students revised AI-generated material more extensively across all disciplines. - Students retained approximately 76% of the AI draft on average. - The roughly 5% who disagreed with the AI’s position revised substantially more, adding more of their own writing. - Only two students submitted the AI draft without edits, despite being explicitly allowed to do so for full credit. ## Implications for Education - Harfe’s exact assignment may not apply to every course, but its underlying principle is broadly useful: incorporate AI into learning activities rather than treating it solely as a threat. - Provenance tools provide a record of writing activity instead of an uncertain verdict about authorship. - The findings challenge the assumption that students will automatically surrender their thinking to AI when given permission to use it. - Students’ willingness to revise appears connected to academic engagement and performance. - Reflective assignments can help students evaluate AI’s strengths, weaknesses, and appropriate future uses. Instructors and institutions should focus less on detecting AI after the fact and more on designing assignments that require students to evaluate, revise, and take responsibility for AI-assisted work.

gen-aiacademic-integritygrammarly-authorshipai-detectors+2

grammarlyMay 22, 2026

How to Write a Salary Negotiation Email: Format and Examples (opens in new tab)

A salary negotiation email is a written counteroffer that helps candidates present their case clearly after receiving a formal job offer. The strongest emails combine market data with two or three measurable accomplishments, state a specific target, and maintain a collaborative tone. If base salary is inflexible, candidates can negotiate other parts of total compensation. ## Preparing Your Case - Research comparable salaries using sources such as Glassdoor, LinkedIn Salary, Payscale, and the Bureau of Labor Statistics. - Choose a specific target or narrow range based on the market, ideally toward the higher end of your acceptable range. - Support the request with quantifiable achievements tied to business outcomes, such as reducing onboarding time by 30% or improving client retention. - Consider the entire compensation package, including: - Signing bonuses - Additional PTO - Remote or hybrid flexibility - Earlier performance reviews - Professional development budgets ## Structuring the Email - Use a clear subject line, such as “Job Offer – [Your Name] – [Role Title]” or “Compensation Discussion – [Your Name].” - Open by thanking the employer and expressing enthusiasm for the role. - Explain the request using market data first, then connect it to relevant experience and accomplishments. - State a concrete counteroffer, such as a target salary or narrow range. - Phrase the request as an invitation to discuss rather than a demand. - Close by reaffirming interest in the position and openness to finding a mutually workable package. ## When to Send It - Negotiate after receiving a formal written offer but before accepting or signing. - If the offer was initially verbal, wait for the written version. - Respond within roughly one to two business days to keep the discussion timely. ## Mistakes to Avoid - Do not rely on vague claims such as having “a lot of experience.” - Avoid personal financial arguments involving rent, expenses, or cost of living. - Do not ask for “something higher” without naming a specific figure. - Avoid demanding or final language that could make the conversation adversarial. - Focus on professional value, relevant market ranges, and the full compensation package. A concise, evidence-based email gives employers a clear reason to reconsider the offer while preserving a positive relationship. Prepare market data and measurable accomplishments in advance, then make a specific, collaborative counteroffer before committing.

grammarlyprofessional-communicationsalary-negotiationcompensation+2

grammarlyMay 22, 2026

How to Reply to a Job Rejection Email, With Examples (opens in new tab)

A thoughtful reply to a job rejection can preserve the relationship, demonstrate professionalism, and keep future opportunities open. The best responses acknowledge the decision, express genuine appreciation, and end with forward-looking language without trying to reverse the employer’s choice. Replies should be concise, personalized, and sent within 24–48 hours after taking time to process the news. ## Understanding Job Rejection Emails - A rejection email informs a candidate they will not advance after applying, screening, or interviewing. - It may be automated and brief or personalized after substantial interaction with the hiring team. - The level of contact should guide how detailed your reply needs to be. ## How to Reply Professionally - **Acknowledge the decision directly:** Begin with a clear statement such as, “Thank you for letting me know about your decision.” - **Show appreciation:** Thank the employer for their time and the opportunity. - **Personalize the message:** Mention one specific project, team detail, or topic discussed during the interview. - **Ask for feedback selectively:** After a substantial interview process, request feedback in a brief, optional way. - **Use forward-looking language:** Express interest in future roles if sincere, or simply wish the team well. - **Keep it concise:** Aim for two or three short paragraphs, use a professional sign-off, and reply in the original email thread. ## When to Send the Reply - Respond within **24–48 hours**. - Take a few hours to process the rejection before writing so the response remains composed. - A reply is usually unnecessary for clearly automated rejections or situations involving minimal interaction. ## Choosing the Right Response - **Early-stage rejection:** Send a short thank-you and ask to be considered for similar future roles. - **Post-interview rejection:** Thank the team, reference a specific discussion point, and express interest in future opportunities. - **Feedback request:** Ask for constructive input without creating pressure to respond. - Personalize each message with details from your experience rather than using a completely generic template. ## Mistakes to Avoid - Re-pitching yourself or arguing against the hiring decision. - Overexplaining your disappointment. - Asking for feedback in a demanding or entitled tone. - Sending an immediate emotional response. - Writing a message that is unnecessarily long. A brief, gracious reply is usually the best approach: thank the employer, personalize the message, and leave the relationship on a positive note.

professional-communicationemail-writingemail-etiquettejob-search+1

grammarlyMay 21, 2026

How to Acknowledge an Email Professionally, With Examples (opens in new tab)

An acknowledgment email briefly confirms that a message was received when a complete reply is not yet possible. The most effective versions identify the specific document or request and provide a next step or response timeframe. Sending one promptly builds trust, prevents unnecessary follow-ups, and keeps work moving. ## Purpose of an Acknowledgment Email - Confirms receipt of an email, document, proposal, or request. - Differs from a full reply because it does not need to answer the underlying request. - Reassures the sender that their message is being handled. ## How to Write One - Keep the original subject line with “Re:” when replying in an existing thread. - Use a descriptive subject for a new thread, such as “Receipt confirmation: Q3 budget proposal.” - Clearly confirm receipt and reference the specific content. - Vague: “Got it, thanks.” - Specific: “Thank you for sending the signed vendor agreement. I’ve received it and will review it this afternoon.” - Set expectations with a deadline or next step, such as “I’ll follow up with feedback by Friday.” - Match the closing and tone to the relationship: - Internal: “Best” or “Thanks” - Formal or client-facing: “Best regards” or “Thank you” ## When to Send One - You received a document, proposal, invoice, contract, or formal request. - The matter is time-sensitive. - You are communicating with a new contact or client. - Someone needs your response before they can proceed. ## When to Skip One - You can provide a complete reply immediately. - The message is low-stakes or purely informational. - You were copied only for awareness and no response is expected. ## Useful Templates - **Simple:** “Got it, I’ll take a look and follow up by [Day]. Thanks.” - **Professional:** Confirm receipt of the document or topic, state when you’ll review it, and mention that you’ll follow up with questions. - **Formal request:** Name the document, confirm the receipt date, and provide a specific review timeframe. - **Job application:** Confirm the application was received and explain when candidates can expect next steps. - **Client or high-stakes matter:** Confirm receipt, identify the team or department handling it, and commit to a specific follow-up date. Send a short, specific acknowledgment whenever a full response will be delayed but the sender needs reassurance. When possible, provide a realistic deadline and meet it.

grammarlyemail-communicationprofessional-writingbusiness-communication

grammarlyMay 18, 2026

How to Write a Follow-Up Email After a Sales Call, With Templates (opens in new tab)

A sales follow-up email keeps a deal moving by reinforcing the call, adding useful information, and proposing one clear next step. The most effective messages are personalized, concise, and sent soon after the conversation. Follow-ups should create momentum rather than merely ask whether the prospect has “had a chance to think.” ## Purpose of a Sales Follow-Up Email - Continues the conversation after a sales call. - Reinforces the prospect’s pain points, goals, and agreed commitments. - Answers open questions and provides relevant resources or insights. - Guides the prospect toward a decision or concrete action. - Differs from a generic check-in because it is directly tied to an active deal. ## Structure of an Effective Follow-Up ### Define the Objective - Review call notes before writing. - Choose one goal, such as confirming a demo, discussing pricing, or scheduling a meeting with a decision-maker. - Keeping the message focused makes it easier for the prospect to respond. ### Write a Specific Subject Line - Reference the conversation: “Next steps from today’s call.” - Highlight value: “Quick recap + the case study I mentioned.” - Mention a specific topic or challenge. - Avoid vague subjects such as “Just checking in.” ### Set the Context - Briefly remind the prospect what you discussed and why you are writing. - Use specific context, such as their onboarding challenge or growth goal. - Avoid generic openings like “Per our conversation” or “Just following up.” ### Recap and Add Value - Summarize the most relevant challenge, goal, or commitment in two or three sentences. - Personalize the message using something the prospect actually said. - Add one useful item, such as a case study, answer, recommendation, or insight. - The new value gives the prospect a reason to respond. ### Request One Clear Next Step - End with a specific, low-friction call to action. - Suggest a time, ask a yes-or-no question, or request confirmation of an agreed action. - Connect the CTA to the call so it feels like a natural continuation. - Avoid vague requests such as “Let me know what you think.” ### Proofread Before Sending - Check grammar, spelling, clarity, and tone. - Ensure the email sounds professional, confident, and helpful. - Read it once for correctness and again from the prospect’s perspective. ## Timing and Follow-Up Cadence - Send the first email within two hours of the call, or by the end of the same business day. - If there is no response, follow up again after three to five days with a new insight or resource. - Send a brief, low-pressure final outreach about a week later. - Use any timeline agreed during the call as the primary guide. - Test different sending times, but maintain consistency because many deals require multiple follow-ups. ## Using Templates Effectively - Templates can provide a reliable structure for common situations, including calls with clear next steps. - A strong template includes: - A personalized reference to the prospect’s challenge - A promised resource or recommendation - A specific proposed action and time - Adapt every template to the actual conversation rather than sending generic copy. The practical recommendation is to send a personalized recap quickly, include something genuinely useful, and ask for one concrete next action. This combination preserves momentum and makes it easier for the prospect to move the deal forward.

grammarlyemail-marketingcrmsales-follow-up+1

grammarlyMay 14, 2026

Email Blast: What It Is and How to Send One, With Templates (opens in new tab)

An email blast sends one message to a large subscriber list, making it effective for promotions, launches, and broad announcements. Its success depends on focused copy, proper timing, audience relevance, and reliable measurement. Blasts maximize reach, but targeted campaigns are better when personalization or behavioral follow-up is needed. ## What an Email Blast Is - A one-time message sent broadly without individual personalization. - Common uses include flash sales, product launches, company news, and announcements. - Unlike an email campaign, it is not usually triggered by behavior or delivered as a sequence. - Blasts and campaigns can work together: a blast introduces the message, while follow-ups target engaged recipients. ## Preparing to Send - Use an email service provider rather than Gmail or Outlook to protect deliverability and comply with sending policies. - Choose a provider with: - Strong deliverability infrastructure - List management for unsubscribes and bounces - Mobile-responsive templates - Analytics for clicks and conversions - Build a permission-based list through opt-ins, purchases, or signup forms. - Avoid purchased or scraped lists, which can damage sender reputation and create legal risks. - Regularly remove invalid, unsubscribed, and consistently bouncing addresses. - Segment subscribers by factors such as purchase history, location, or engagement to improve relevance. ## Writing Effective Blast Copy - Give the email one clear goal, one central message, and one action. - Write a specific subject line that communicates a benefit or outcome. - Keep body copy concise, scannable, and focused on the reader’s benefit. - Use one prominent call to action that clearly explains what recipients should do. - Send from a recognizable brand or person to build trust. ## Compliance Requirements - Ensure the subject line accurately reflects the email. - Clearly identify the sender. - Include a valid physical mailing address. - Provide an easy-to-use unsubscribe link and honor requests promptly. - Account for regional requirements such as CAN-SPAM, GDPR, and CASL. ## Timing and Measurement - Midweek mornings often perform well, but the best timing varies by audience and industry. - Test different days and times with smaller groups before sending to the full list. - Track click-through rate and conversion rate to evaluate performance. - Treat open rate cautiously because privacy features such as Apple Mail Privacy Protection can make it unreliable. - Use results to refine subject lines, send times, and calls to action. ## When to Use an Email Blast - Use blasts for messages relevant to a broad audience, including: - Time-sensitive promotions - Product launches - Company-wide announcements - Avoid relying on blasts when subscribers need individualized communication, such as onboarding or re-engagement. A successful email blast combines a clean, permission-based list with concise benefit-driven copy, one clear CTA, compliance, and ongoing testing. For more personalized needs, use segmentation or a behavior-based email campaign instead.

conversion-rate-optimizationgdpremail-marketingemail-blast+4

grammarlyApr 30, 2026

Educator of the Year (opens in new tab)

Grammarly’s inaugural Educator of the Year Award honors teachers nominated directly by their students. The first winner, Dr. Humberto López Castillo of the University of Central Florida, is recognized for teaching precise, accessible communication and applying it to public health, technology, and community engagement. His approach combines audience-aware writing, responsible AI use, and hands-on research. ## Student-Led Recognition - Students nominate educators through short videos describing their impact on academic and professional development. - UCF student Vardhan Avaradi nominated Dr. López Castillo for encouraging students to make their language “precise yet accessible.” - López Castillo is a pediatrician, public health researcher, translator, and four-language polyglot from Panama. - His teaching emphasizes collaboration and the connection between individual health and broader communities. ## Communicating With Different Audiences - Students translate complex public health topics for audiences outside academia. - Assignments have included: - Storybooks about mosquitoes for kindergarteners - Monopoly-style games about living with HIV - Rap songs explaining tuberculosis - Podcasts that personalize epidemiology - His medical experience informs this approach: communication must change depending on whether the audience is a child, parent, or professional researcher. ## AI Requires Human Judgment - López Castillo permits students to use AI for drafting but expects them to verify and critically evaluate its output. - When AI-generated citations referenced nonexistent research, he treated the error as a lesson rather than a punishment. - He compares AI to a calculator: useful and powerful, but dependent on the judgment of the person using it. - He and Vardhan are developing a machine learning project using the NIH All of Us dataset, which contains nearly one million de-identified health records. - Their research explores using AI to classify populations and predict health risks. ## Preparing Students for Broader Impact - Students leave with stronger writing, critical-thinking, collaboration, and communication skills. - López Castillo’s teaching focuses not just on adopting new tools, but on using them responsibly and communicating with purpose. - His students learn to reach people beyond academic audiences while keeping human needs at the center of technology and research. The post’s central recommendation is to pair emerging technologies with critical thinking, audience awareness, and a strong sense of social responsibility.

aidatabase-designmachine-learningpublic-health+3

grammarlyApr 16, 2026

The Trust Practice: What Building Credibility Requires (opens in new tab)

Trust in education is not universal; it depends on stakeholders’ responsibilities and the risks they carry. Research across K–12 and higher education shows that AI systems earn trust when they provide clarity about safety, accountability, autonomy, and professional judgment. Effective AI governance must therefore be context-aware rather than based solely on general principles such as transparency or user control. ## K–12: Trust as Stewardship - Educators and administrators prioritize student safety, parental expectations, and institutional duty of care. - Their central question is whether a system will protect students and the institution when problems arise. - Trust grows through clear guardrails, oversight, data protections, and shared responsibility. - Ambiguity around accountability or student information can quickly undermine confidence. ## Higher Education: Trust as Autonomy and Credibility - Faculty and administrators focus on academic integrity, authorship, intellectual ownership, and professional expertise. - They ask whether AI supports or undermines their role as scholars and educators. - Trust is connected to autonomy and the legitimacy of learning itself. - A tool that feels safe in K–12 may feel threatening in higher education because the stakes and responsibilities differ. ## Why Context Matters for AI Adoption - Transparency, explainability, and user control are necessary but do not automatically create trust. - Systems must align with the actual responsibilities educators manage. - Poor alignment can lead to hesitation, stricter governance, and stalled adoption. - The same AI behavior may build trust in one setting while eroding it in another. ## What Educators Need - Educators consistently ask for clarity rather than generic reassurance: - What is the system doing? - Who is accountable when it fails? - How will it affect students, professional judgment, and authorship? - Do educators retain decision-making authority? - Institutional governance, communication, and even silence signal what an institution values and whom it trusts. - Leaders need partners who can acknowledge uncertainty and complexity instead of oversimplifying them. ## Building Trust Over Time - Trust develops through consistent behavior, honest risk management, and meaningful responses when things go wrong. - AI platforms serving multiple education sectors should be context-aware, role-sensitive, and explicit about responsibility. - Design, governance, and messaging that work in one environment may create friction in another. - Treating trust as a universal feature risks overlooking the people accountable for using the technology. AI in education should be designed around the distinct responsibilities of educators and institutions. Trust is not something that can be built once and shipped; it must be earned through clear accountability, contextual design, and sustained partnership.

data-privacyai-governancesystem-designeducation-technology+3

grammarlyApr 13, 2026

The Trust Question: How Higher Education Is Really Navigating AI (opens in new tab)

Higher education’s AI challenge is fundamentally a question of trust, not simply technology adoption or resistance. Based on interviews with educators and administrators, institutions are balancing competing views about innovation, evidence, ethics, and practical outcomes. The central conclusion is that credible AI governance must make these differences visible and build shared understanding rather than rely on blanket rules or binary narratives. ## AI Policy Is a Campus-Wide Negotiation - Four recurring orientations shape institutional responses: - **Innovators** favor responsible adoption before reactive governance becomes necessary. - **Strategists** want stronger evidence before committing to change. - **Resisters** prioritize ethics, academic integrity, and institutional reputation. - **Pragmatists** focus on student success, equity, and workable implementation. - These perspectives often coexist within the same institution. - Differences between administrators, writing center leaders, and faculty can create productive debate or direct conflict. - Recognizing these mindsets helps institutions engage stakeholders more effectively. ## Institutions Need Alignment, Not More Tools - Leaders consistently asked for alignment with institutional priorities, constraints, and values—not additional technology. - Effective partners should help institutions understand trade-offs rather than impose preselected solutions. - Skeptics need language that allows them to raise concerns constructively. - Advocates for adoption must recognize that resistance often reflects responsibility rather than fear of change. - AI is forcing institutions to clarify long-standing tensions such as: - Speed versus rigor - Access versus control - Innovation versus stability ## Academic Integrity as a Trust Problem - The common starting question—how to prevent students from misusing AI—is too narrow. - Academic integrity also asks whether institutions trust students and whether students trust their institutions. - Excessive restrictions can communicate distrust, while a lack of governance can appear negligent. - K–12 and higher education face different accountability structures, but both must create guidelines that reflect their actual educational values. - Many educators are shifting: - From detection to judgment - From surveillance to discernment - From punishment to responsibility - Integrity policies therefore communicate what an institution believes learning is for. ## Governing Under Uncertainty - Leaders are tired of portraying AI as either an existential threat or a universal solution. - They need principled language for discussing uncertainty with students, faculty, families, and governing boards. - Every AI decision sends a message about institutional values and credibility. - Maintaining trust requires thoughtful governance, shared understanding, and honest engagement with uncertainty—not stricter rules alone. Institutions should treat AI governance as an ongoing process of alignment and trust-building. Rather than beginning with enforcement or technology procurement, they should clarify their values, acknowledge competing perspectives, and develop policies that support informed judgment and shared responsibility.

aiacademic-integrityedtechchange-management+3

grammarlyMar 27, 2026

What Is AI Chat? Definition, How It Works, and Key Benefits (opens in new tab)

AI chat enables open-ended, context-aware conversations with systems that generate responses dynamically rather than following fixed scripts. Powered by large language models (LLMs), it supports tasks such as writing, brainstorming, learning, summarizing, planning, and coding. Its flexibility comes with limitations: responses reflect learned patterns rather than true understanding, so users should provide clear context and verify results. ## What AI Chat Is - AI chat allows users to ask questions naturally and refine requests through follow-up messages. - It can answer questions, explain complex subjects, draft and revise text, summarize documents, generate code, and provide feedback. - Unlike fixed chatbot flows, it handles unstructured requests and evolving conversations without requiring users to restart. ## How AI Chat Works - **LLM training:** Models learn language patterns from massive text datasets rather than memorizing a fixed set of answers. - **Natural language processing:** The system analyzes prompts to infer meaning, intent, tone, and context beyond exact keyword matches. - **Response generation:** The model predicts and selects text one word at a time based on the prompt and patterns learned during training. - **Conversation context:** Recent messages help the system interpret follow-up requests, such as understanding that “make it shorter” refers to a previously generated summary. - **Ongoing refinement:** Fine-tuning and human feedback improve safety, accuracy, and alignment. Models generally do not learn from individual conversations in real time. ## AI Chat Compared with Traditional Chatbots - Traditional chatbots commonly use rules, decision trees, and scripted responses. - They work well for narrow, repeatable tasks such as FAQs, appointment booking, and order tracking. - AI chat is better suited to open-ended activities including brainstorming, drafting, explanations, and problem-solving. - “Conversational AI chatbot” usually describes a chatbot interface powered by generative AI, making it more flexible than a fully rules-based system. ## Common Uses - **Writing and editing:** Draft emails, rewrite passages, adjust tone, improve clarity, and revise reports or presentations. - **Brainstorming:** Generate ideas, outlines, alternatives, and new perspectives through iterative discussion. - **Learning and planning:** Explore unfamiliar topics, simplify complex information, and develop plans. - **Coding support:** Generate code, explain technical concepts, and help troubleshoot problems. ## Effective Use - Write clear prompts and provide relevant context. - State the goal, desired format, audience, and preferences. - Use follow-up questions to refine the response. - Review outputs for factual errors, bias, and inappropriate assumptions. AI chat is most useful as a flexible assistant rather than an unquestionable authority. Use it for exploration and productivity, but verify important information and apply human judgment before relying on its output.

llmmachine-learningnlpworkflow-automation+4

grammarlyMar 27, 2026

How to Create a Chatbot Step by Step: A Beginner’s Guide (opens in new tab)

Chatbot development begins with a focused purpose, not technology. By choosing the right interaction method, chatbot type, and platform, organizations can automate routine tasks and improve user experiences without necessarily needing developers. Successful chatbots also require deliberate conversation design, testing, monitoring, and continuous improvement. ## What Chatbots Can Do - Simulate conversations through text or voice. - Answer frequently asked questions and provide information. - Handle structured tasks such as: - Checking order status - Booking appointments - Explaining policies - Guiding users through onboarding - AI-powered and hybrid chatbots can manage follow-up questions and more complex, multistep interactions. - They can reduce repetitive work, improve response consistency, and help users reach solutions faster. ## Define the Chatbot’s Goal - Identify two or three specific tasks the chatbot should handle. - Define the target audience, such as customers, employees, or students. - Establish success metrics, including: - Fewer support tickets - Faster response times - Higher task-completion rates - A narrow, well-defined purpose makes the chatbot easier to design, test, and refine. ## Choose the Interaction Method - Decide whether the chatbot will be text-based or voice-based. - Text is generally simpler to build. - Voice requires additional technical setup. - Choose where it will operate, such as: - A website - Mobile application - Messaging platform - Internal company tool - Determine how conversations begin, whether through typed messages, preset options, or proactive prompts. - The access point and interaction style directly affect development and maintenance requirements. ## Select the Chatbot Type - **Rule-based chatbots** use predefined flows, menus, and decision trees for predictable requests. - **Keyword-based chatbots** respond to specific words or short phrases, such as “pricing” or “hours.” - **AI chatbots** use artificial intelligence and natural language processing to handle varied questions and contextual follow-ups, but require more testing and oversight. - **Hybrid chatbots** combine structured rules for common tasks with AI for open-ended questions. - The choice determines the chatbot’s flexibility, behavior, complexity, and ongoing management effort. ## Choose a Building Platform - **No-code platforms** such as Chatling, Voiceflow, Zapier, and Landbot use visual interfaces and are suitable for beginners and simple chatbot tasks. - **Low-code or full-code approaches** using technologies such as Python, Node.js, or AI frameworks provide greater customization and integration capabilities. - Platform selection should account for: - Cost - Integrations - Analytics - Scalability - Data protection - Required technical expertise ## Design the Conversation Flow - Map typical conversations before implementing the chatbot. - Planning helps identify missing responses, avoid dead ends, and create a smoother user experience. - Traditional chatbots generally use structured decision paths, while AI chatbots support more flexible conversations. - The flow should reflect the chatbot’s purpose and provide a clear route for completing tasks or escalating complex issues. ## Ongoing Improvement - Building and launching the chatbot is only the beginning. - Chatbots should be tested before release and monitored afterward. - Regular refinement, accurate training data, configuration updates, and performance reviews help maintain quality over time. A practical approach is to start with a narrow use case and a simple platform, then expand as user needs and performance data become clearer. Choose AI or custom development only when the chatbot requires more flexibility, deeper integrations, or complex conversational capabilities.

database-designnlpuser-experience-designno-code-tools+3

grammarlyMar 26, 2026

What Is a Chatbot? Definition, Types, and Examples (opens in new tab)

Chatbots are conversational interfaces that use text or voice to answer questions, provide information, and help users complete tasks. They range from predictable rule- and keyword-based systems to flexible AI-powered tools that generate responses dynamically. Their main advantages are speed, consistency, and scalability, but flexibility and accuracy depend on how they are designed. ## What Chatbots Are - Chatbots simulate human conversation through text or voice. - They let users ask questions or make requests without navigating menus or fixed workflows. - Common applications include websites, mobile apps, messaging platforms, customer support, and help centers. - A chatbot is the user-facing interface; conversational AI provides language-understanding capabilities; and virtual assistants are broader tools that use conversation to perform tasks. ## Main Types of Chatbots ### Rule-Based Chatbots - Follow predefined decision trees and fixed conversation paths. - Commonly use buttons or menus such as “Billing” and “Technical support.” - Provide consistent, predictable responses. - Struggle with unexpected questions or requests outside their programmed workflows. ### Keyword-Based Chatbots - Detect specific words or phrases and return associated responses. - For example, the word “refund” might trigger a returns-policy link. - Allow free-text input but do not truly understand intent. - Can fail when users phrase requests differently from expected keywords. ### AI Chatbots - Use machine learning, natural language processing, and large language models to interpret requests. - Generate responses dynamically rather than selecting only from predefined answers. - Can handle loosely phrased questions, follow-up messages, complex explanations, and tone adjustments. - Responses may vary and should be checked for accuracy and relevance. ### Hybrid Chatbots - Combine structured rules with AI-generated responses. - May use menus to route common requests and AI for more complex follow-up questions. - Balance predictable task handling with conversational flexibility. ## How Chatbots Work - **Receive input:** The system captures a typed message or spoken request. - **Interpret the request:** Rule-based systems follow pathways, keyword systems match terms, and AI systems analyze intent and context. - **Generate a response:** The chatbot provides information, a next step, a predefined reply, or an AI-generated answer. - The overall process is similar across chatbot types, but the method used to interpret messages and produce responses differs significantly. ## Benefits and Limitations - Chatbots can deliver fast responses, provide consistent information, scale across many users, and automate routine interactions. - They can guide users through tasks, answer common questions, and reduce reliance on human support. - Rule- and keyword-based systems are reliable within narrow, predefined scenarios but lack flexibility. - AI chatbots handle broader conversations more naturally but may produce inaccurate or inconsistent answers. - Choosing the right chatbot type depends on whether predictability, flexibility, task automation, or open-ended conversation is most important. A practical chatbot strategy matches the technology to the task: use structured systems for predictable workflows, AI for nuanced conversations, and hybrid designs when both reliability and flexibility are needed.

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grammarlyMar 11, 2026

Now Available: Grammarly’s Writing Support in 17 More Languages (opens in new tab)

Grammarly’s latest Beta expansion adds real-time grammar and spelling corrections for 17 languages, bringing support to more than 20 languages overall. The feature works automatically in Grammarly’s browser extension and Desktop app, helping users write, edit, and collaborate across languages. More advanced clarity, fluency, tone, and reading-translation features are planned. ## Expanded Language Support - Newly supported languages include: - Turkish, Polish, Dutch, Czech, Vietnamese, Hungarian, Swedish, Romanian, Indonesian, Slovak, Danish, Finnish, Norwegian, Ukrainian, Korean, Tagalog, and Hindi. - These additions build on existing support for Spanish, French, German, Portuguese, and Italian. - Current Beta functionality focuses on grammar and spelling corrections. - Corrections appear in real time without additional setup or settings changes. ## Translation Across Languages - Grammarly provides in-line translation across 19 languages. - Users can highlight text, open the blue sidebar, and choose a target language. - The feature supports drafting and editing in multiple languages without interrupting workflow. ## Planned Improvements - Grammarly plans to add clarity, fluency, and tone suggestions to the 17 newly supported languages. - During the Beta period, the company will refine its models to achieve consistent quality across languages. - A planned reading-assistance feature will let browser-extension users highlight text and translate it while reading, rather than switching tabs. ## Getting Started - Sign up for or log in to a Grammarly account. - Open the Grammarly browser extension or Desktop app. - Write in any supported language to receive real-time corrections.

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