Tag: internal

Why Irish Tech Companies Are Failing at Sustainability Marketing

The €4.2 Million Greenwashing Fine That Changed Everything

When the Competition and Consumer Protection Commission hit a prominent Irish software company with a multimillion-euro fine for misleading environmental claims, boardrooms across Dublin’s tech corridor went silent. The message was clear: vague sustainability promises and manufactured green credentials no longer fly in an era of radical transparency.

Irish tech companies, from fintech startups in Cork to medtech innovators in Galway, often run genuinely sustainable operations. They’ve achieved carbon neutrality, eliminated single-use plastics, and built products helping other businesses reduce environmental impact. Yet their sustainability communications fail so spectacularly that consumers trust them less than traditional industries with worse environmental records.

The problem isn’t lack of green initiatives—it’s the disconnect between operations and communications. While engineering teams measure server efficiency to the kilowatt-hour, marketing departments resort to clichés about “saving the planet” that trigger scepticism. ProfileTree identifies this communication gap as why Irish tech companies struggle to monetise genuine sustainability investments through improved brand perception.

The Data Behind Tech’s Sustainability Crisis

Analysis of 200 Irish tech websites reveals disturbing patterns. Seventy-eight percent use identical phrases—”committed to sustainability,” “reducing our carbon footprint”—meaningless through overuse. Only 12% provide measurable environmental data. Most damning: 91% bury sustainability information in footers rather than integrating it into value propositions.

Irish consumers rank environmental responsibility as their third-highest purchase criterion for tech products. Yet when surveyed, they couldn’t identify a single Irish tech brand as sustainability leaders. This perception gap represents billions in lost brand value.

Tech companies with verified, well-communicated sustainability credentials see 23% higher retention rates and command 18% price premiums. Those caught greenwashing face 18-month recovery periods. Effective sustainability communication has become existential rather than optional.

Why Traditional Marketing Fails

Tech companies list environmental certifications like software specifications, expecting customers to value ISO 14001 compliance. This engineering-driven style fails because consumers don’t buy certifications—they buy authentic stories resonating with values.

The velocity of change compounds challenges. While manufacturing companies celebrate the same renewable installation for years, tech companies constantly evolve initiatives. Marketing teams struggle keeping pace with improvements across Dublin, Cork, Limerick offices.

Cultural misalignment creates friction. Tech marketing emphasises innovation and competitive advantage—messages conflicting with sustainability’s collaborative nature. This produces confused messaging satisfying neither advocates nor growth-focused stakeholders.

AI Revolution in Sustainability Storytelling

Artificial intelligence transforms sustainability marketing from guesswork into science. Natural language processing analyses millions of conversations, revealing which messages resonate. Irish consumers respond to local environmental impact but dismiss global climate messaging as abstract.

Machine learning identifies unexpected narratives within operational data. A Dublin SaaS company discovered their platform prevented 2.3 million commute miles annually—more compelling than carbon-neutral hosting. An Irish cybersecurity firm found their algorithms reduced client energy consumption by preventing cryptomining malware.

Predictive analytics determine optimal timing for communications, avoiding “green fatigue” whilst maintaining visibility. This precision targeting ensures messages reach sympathetic audiences, improving engagement and conversions.

Building Credible Narratives That Convert

Effective sustainability marketing strategies begin with transparency about achievements and shortcomings. A Galway software company increased trust 40% by publishing detailed reports including failures, not just victories.

Specificity replaces vagueness. Instead of “reducing emissions,” successful companies state “our Dublin data centre runs on Arklow Bank wind power, preventing 2,400 tonnes CO2 annually.” These concrete claims, backed by verification, build trust incrementally.

Employee voices amplify messages better than corporate statements. Engineers explaining code optimisation, managers describing waste reduction—authentic perspectives resonate more than polished copy. Companies leveraging employee advocacy see 3x higher engagement on sustainability content.

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The Technology Stack for Communications

Modern sustainability marketing requires sophisticated infrastructure. Carbon accounting provides real-time data. Blockchain creates immutable records. IoT sensors capture granular environmental metrics.

Integration between measurement and automation enables dynamic communications. When renewable usage peaks, systems update badges, trigger posts, notify customers. Cork tech companies using integrated platforms report 50% reduction in reporting costs whilst improving accuracy.

AI-powered content tools help teams maintain consistent communications without dedicated headcount. Systems transform technical data into accessible stories. However, human oversight ensures authenticity before publication.

Measuring What Matters

Traditional metrics fail capturing effectiveness. Trust scores and reputation indices matter more than clicks. Irish tech companies need frameworks connecting messaging to outcomes over extended timeframes.

Sentiment analysis provides nuanced understanding. A Limerick company discovered high-traffic content actually damaged perception by appearing self-congratulatory.

Attribution modelling reveals true impact. Customers exposed to authentic content show 31% higher lifetime values over months. Without sophisticated measurement, companies underinvest, missing revenue opportunities.

Navigating Regulatory Requirements

The EU Green Claims Directive changes requirements fundamentally. Vague claims face fines up to 4% of global turnover. Companies must implement verification ensuring claims withstand scrutiny.

Life cycle assessments become mandatory. Tech companies must account for entire product lifecycles. A Dublin startup discovered their “eco-friendly” device generated more emissions due to shorter replacement cycles.

Third-party verification provides essential credibility. Verified claims generate 5x more trust than self-reported metrics. Smart companies view verification as insurance against reputational damage.

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Sector-Specific Strategies

Different sectors require tailored approaches. Fintech emphasises how digital banking reduces infrastructure. Medtech highlights remote monitoring reducing patient travel. Agtech demonstrates precision agriculture reducing chemical inputs.

B2B companies focus on helping clients achieve goals. Enterprise software quantifies client carbon reduction. This customer-centric approach transforms sustainability from cost to revenue driver.

Consumer-facing companies need emotional narratives. Gaming companies highlight digital distribution eliminating waste. EdTech emphasises democratising education without travel. Human-centred stories resonate more than metrics.

AI-Powered Training for Teams

Marketing teams need comprehensive training, but traditional workshops fail keeping pace. AI-powered corporate training delivers personalised, continuously updated education ensuring teams remain current.

Adaptive systems identify knowledge gaps, focusing on specific weaknesses. Irish companies using AI training report 60% faster competency development.

Simulation environments allow practicing without risk. Teams trained through simulations handle challenges 40% more effectively than those relying on theory.

Building Internal Alignment

Sustainability marketing fails when disconnected from reality. Marketing needs integration with operations to communicate authentic achievements.

Regular workshops bring diverse teams together identifying narratives. Engineers explain improvements accessibly. Product managers describe design decisions. These sessions generate authentic content whilst building commitment.

Executive sponsorship proves crucial. When CEOs champion initiatives, authenticity follows. Waterford companies with CEO-led programmes see 4x better outcomes.

Future-Proofing Your Strategy

Emerging regulations require greater transparency. CSRD mandates detailed disclosures. Digital Product Passports track lifecycles. Companies building infrastructure now will navigate smoothly whilst competitors scramble.

Blockchain will revolutionise verification. Smart contracts compensate offsets automatically. Irish companies should explore integration preparing for this transparent future.

Consumer expectations escalate beyond current standards. Gen Z demands regenerative models improving conditions. They expect real-time data and participation in decisions. Companies must evolve from communication to conversation.

Your 90-Day Transformation

Start with honesty about current communications. Audit content for greenwashing risk. Remove questionable content—silence beats deception. Rebuild narratives based on verified data.

Invest in measurement before campaigns. Implement carbon accounting, establish baselines, create verification. This foundation enables credible communications.

Partner with experts understanding sustainability complexity and tech dynamics. The sweet spot combines sustainability expertise, marketing sophistication, and industry experience. These combinations deliver strategies satisfying regulators, resonating with customers, driving results.

The path from greenwashing risk to leadership requires commitment beyond tactics. For Irish tech companies embracing authentic sustainability marketing, rewards include reputation, loyalty, and alignment between commercial success and environmental necessity.

 

How Top Agencies Use Visual Annotation to Cut Delivery Times by 40%

Feedback can make or break a project timeline. It’s often not the creative work that slows things down—it’s the endless cycle of revisions, miscommunications, and the frustrating hunt for clarity. Agencies trying to deliver high-quality websites or digital experiences often find themselves bogged down not by the work itself, but by how feedback is managed.

And that’s where visual annotation tools are changing the game.

What Slows Agencies Down? It’s Not Just the Workload

A lot of agencies have tight internal systems. They use project management tools, they run stand-ups, they track deadlines with discipline. But when it comes to collecting and actioning client feedback, even the most organized teams hit a wall.

Think of it this way: your client sends an email that says, “Can you fix the spacing on that thing under the testimonial?” Suddenly, a developer is opening three different browsers, resizing their screen, and still isn’t sure what that thing actually is. Multiply that by a dozen pieces of vague feedback and now your team is spending more time decoding than developing.

Why Visual Feedback Changes Everything

Visual annotation tools let clients drop comments directly onto a live site, wireframe, or image—pinpointing exactly what they mean. It’s like placing a digital sticky note on a specific button, section, or layout element. But it’s not just about convenience. These tools typically capture screenshots, browser data, screen resolution, and even the device used—all automatically.

So, instead of asking “Which version of Chrome are you using?” or “What did it look like on your end?”, your team has everything they need from the get-go.

Less guessing. Less back-and-forth. Way faster fixes.

How Agencies Are Actually Using These Tools

For a growing number of web and creative agencies, visual annotation tools aren’t just nice-to-have—they’re core to their workflow.

During the QA phase, project managers use them to review builds internally before involving clients. Designers gather precise change requests during the approval process. Developers get all the context they need to resolve bugs quickly. And clients? They finally feel like their feedback is being heard and acted on—without having to send long-winded emails.

Many agencies also loop stakeholders in without forcing them to create an account or learn a new system. A simple shared link is often all it takes to bring someone into the review process. It’s feedback made easy—for everyone involved.

From Two Weeks of Back-and-Forth to Two Days of Clarity

One agency we spoke to used to spend about 10–14 days just gathering and clarifying feedback for a mid-sized web project. After adopting a visual annotation system, they saw that drop to less than three days.

They didn’t rush the creative. They just cut out the lag time between misaligned feedback, miscommunication, and confusion. Multiply that time savings across several projects and it’s easy to see how 40% faster delivery isn’t just possible—it’s practical.

Yes, There Are Tools. But Not All Are Equal

If you’ve searched for markup alternatives, you’ve probably come across a few popular platforms offering visual collaboration features. Some are geared toward developers, some toward designers, and some offer feedback on a range of media—from PDFs to video.

But here’s what top agencies really look for:

  • A way to drop comments in context—on the actual site or design
  • Automatic capture of screenshots and technical specs
  • A smooth way to turn comments into tasks
  • No need for client logins or complicated onboarding
  • Integration with tools they already use, like Trello, Asana, or Jira

The best visual annotation tools don’t just help you collect feedback—they plug into your process like they were always meant to be there.

Why It’s Not Just About Speed

Faster delivery is a big win, no question. But agencies are also seeing softer benefits. Clients feel more involved and confident throughout the build. Team members feel less frustrated chasing down unclear comments. And projects, overall, just feel smoother.

That kind of workflow creates happier clients and happier teams. And, let’s be honest—when your team isn’t spending hours rewriting feedback as tasks or jumping between email threads, they have more creative energy to put into what really matters.

Cutting Through the Noise

Agencies aren’t strangers to project chaos. But the smartest ones are finding ways to cut through the noise—to align their teams, clients, and tools in a way that brings clarity and flow.

Visual annotation is more than a helpful add-on. For many, it’s become the cornerstone of a modern feedback process. It brings everyone onto the same page—literally—and gives teams the confidence to move fast without sacrificing quality.

Because when feedback stops being a bottleneck, delivery becomes a whole lot easier.

 

AWS Announces General Availability of Amazon Q

Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company (NASDAQ: AMZN), today announced the general availability of Amazon Q, the most capable generative artificial intelligence (AI)-powered assistant for accelerating software development and leveraging companies’ internal data. Amazon Q not only generates highly accurate code, it also tests, debugs, and has multi-step planning and reasoning capabilities that can transform (e.g., perform java version upgrades) and implement new code generated from developer requests. Amazon Q also makes it easier for employees to get answers to questions across business data such as company policies, product information, business results, code base, employees, and many other topics by connecting to enterprise data repositories to summarize the data logically, analyze trends, and engage in dialog about the data. Today, AWS is also introducing Amazon Q Apps, a new and powerful capability that lets employees build generative AI apps from their company’s data. Employees simply describe the type of app they want, in natural language, and Q Apps will quickly generate an app that accomplishes their desired task, helping them streamline and automate their daily work with ease and efficiency. To learn more about Amazon Q, visit aws.amazon.com/q.

“Amazon Q is the most capable generative AI-powered assistant available today with industry-leading accuracy, advanced agents capabilities, and best-in-class security that helps developers become more productive and helps business users to accelerate decision making,” said Dr. Swami Sivasubramanian, vice president of Artificial Intelligence and Data at AWS. “Since we announced the service at re:Invent, we have been amazed at the productivity gains developers and business users have seen. Early indications signal Amazon Q could help our customers’ employees become more than 80% more productive at their jobs; and with the new features we’re planning on introducing in the future, we think this will only continue to grow.”

Amazon Q Developer

Today, developers tell us that only 30% (or less) of their time is spent on coding, while the rest is spent performing tedious and repetitive tasks. This could be researching best practices from various parts of the web or learning how things work through documentation, forums, and conversations with colleagues. Developers also have to manage infrastructure and resources, troubleshoot and resolve errors, and understand operating costs. When they switch projects, they have to spend time learning the existing code base to understand its programming logic. Finally, there is all the work of testing and refactoring code, upgrading applications, debugging and optimization, and ensuring security by having to carry out vulnerability scanning and applying appropriate security fixes in a timely fashion. Companies want to empower their developers to spend less time on this coding muck and more time on creating unique experiences for their end users, while being able to deploy faster.

Q assists developers and IT professionals (IT pros) with all of their tasks—from coding, testing, and upgrading applications, to troubleshooting, performing security scanning and fixes, and optimizing AWS resources. Amazon Q delivers advanced and tailored generative AI capabilities, including:

  • Most accurate coding recommendations: Amazon Q helps developers build faster and more securely by generating code suggestions and recommendations in near real time. Customers such as Blackberry, BT Group, and Toyota are already using Q to increase developer productivity and speed up innovation in their organizations. Amazon Q Developer has the highest reported code acceptance rates in the industry, for assistants that perform multi-line code suggestions, with BT Group recently sharing that they accepted 37% of Q’s code suggestions and National Australia Bank reporting 50% acceptance rates. Q also has a powerful customization capability that securely leverages a customer’s internal code base to provide more relevant and useful code recommendations. With this capability, Q is an expert on your code and provides recommendations that are more relevant to save even more time. Q keeps customizations completely private, and the underlying FM does not use them for training, protecting customers’ valuable intellectual property.
  • Amazon Q Developer Agents: Q has a unique capability, called agents, which can autonomously perform a range of tasks–everything from implementing features, documenting, and refactoring code, to performing software upgrades. Developers can simply ask Amazon Q to implement an application feature (such as asking it to create an “add to favorites” feature in a social sharing app), and the agent will analyze their existing application code and generate a step-by-step implementation plan. Developers can collaborate with the agent to review and iterate on the plan before the agent implements it, connecting multiple steps together and applying updates across source files, code blocks, and test suites. Carrying out these tasks, Q has achieved the highest scores of any software development assistant available today, scoring 13.4% on the SWE-Bench Leaderboard and 20.5% on the SWE-Bench Leaderboard (Lite), a dataset that benchmarks coding capabilities.

To save customers months, even years, of time upgrading applications, Q can also automate and manage the entire upgrade process–with Java conversions available today and .Net conversions coming soon to help people move from Windows to Linux. In their IDE, developers simply ask Amazon Q to “transform” their project and the agent analyzes application source code, generates new code in the target language or version, executes tests, and completes all code changes. A five-person team at Amazon used Q to upgrade more than 1,000 production applications from Java 8 to Java 17 in just two days (the average time per application was less than 10 minutes), saving months of time, and improving application performance–previously, many of these applications would each take a couple of days to upgrade.

  • Best-in-class security vulnerability scanning and remediation: Q scans code for hard-to-detect vulnerabilities, such as exposed credentials and log injection. With a single click, Q automatically suggests remediations tailored to the application code, allowing developers to quickly accept fixes with confidence. Q’s security scanning capabilities outperform leading publicly benchmarkable tools on detection across most of the popular programming languages, helping to significantly improve the security and code quality of a developer’s application.
  • Q is an expert on AWS and optimizing your AWS environment: Amazon Q Developer is an expert on AWS and is in the console to help IT pros optimize their cloud environments, as well as diagnose and resolve errors and networking issues, select instances, optimize structured query language (SQL) queries, extract, transform, and load (ETL) pipelines, and provide guidance on architectural best practices. To further help customers optimize their cloud environments, today Amazon Q Developer includes a new feature that helps customers list their AWS account resources, configurations, and analyze billing information and trends, making it easier for them to manage their accounts. For example, IT pros can simply ask, “What instances are currently running in US East 1?” or “What’s my S3 bucket encryption?” or “What were my EC2 costs by region last month?” and Amazon Q Developer will list the resources and details in a summarized answer with links to learn more.

 

Amazon Q’s conversational interface is available wherever it is needed—in the AWS Console, in Slack, or in IDEs, including Visual Studio Code and JetBrains–to give developers the ability to use the conversational experience of Q within their favorite software development solutions. To extend the Q experience to more places developers work, AWS is announcing new partner extensions from Datadog and Wiz, and an integration with GitLab Duo that will offer joint customers a unified interface—whether working in AWS or GitLab.  By integrating Amazon Q’s generative AI capabilities with solutions that developers know, use, and trust, developers can update and create software faster.

Amazon Q Business

Organizations possess vast amounts of data spread across multiple documents, systems, and applications. Employees across every organization and department spend hours every week searching internal sources for information, piecing together analyses, writing reports, building presentations, gathering insights from dashboards, and adapting content for different audiences. Generative AI can help solve these challenges. However, the offerings available today are not connected to business data or internal resources and are not built from the ground up with security in mind. Because of these barriers, many organizations cannot safely tap into the full potential of generative AI.

Q Business is a generative AI–powered assistant that can answer questions, provide summaries, generate content, and securely complete tasks based on data and information in your enterprise systems. It empowers employees to be more creative, data-driven, efficient, prepared, and productive:

  • Q unites more data sources than any other generative AI assistant available today: Amazon Q Business easily and securely connects to 40+ commonly used business tools, such as wikis, intranets, Atlassian, Gmail, Microsoft Exchange, Salesforce, ServiceNow, Slack, and Amazon Simple Storage Service (Amazon S3)–more than any other generative AI assistant available today. Simply point Q at your enterprise data repositories, and it will search all of your data, summarize logically, analyze trends, and engage in dialog with end users about the data. This helps business users to access all of their data, no matter where it resides in their organization.
  • Built from the ground up with security and privacy in mind: Amazon Q Business seamlessly integrates with a customer’s existing identities, roles, and access permissions to personalize the interactions for each individual user, while maintaining the highest levels of security. It generates accurate responses based on enterprise information, and customers can restrict sensitive topics, block keywords, and filter out inappropriate content. Q also does not use customer content to train the underlying models for anybody else. Amazon Q Business outperforms all published results for other assistants on correctness, truthfulness, and helpfulness for general Q&A (using the MultiHop-RAG dataset), as well as industries like finance (using a FiQA dataset sample) and technology (using a LoTTE dataset sample).
  • Inventive generative BI allows analysts to build detailed dashboards in minutes and business users to get insights fast: Amazon Q brings its advanced generative AI technology to Amazon QuickSight, AWS’s unified Business Intelligence (BI) service built for the cloud. With Amazon Q in QuickSight, customers get a Generative BI assistant that allows business analysts to use natural language to build BI dashboards in minutes and easily create visualizations and complex calculations. It is also the only BI product where business users can get AI-driven executive summaries of dashboards, ask questions of data beyond what is presented in the dashboards, and create detailed and customizable data stories highlighting key insights, trends, and drivers. Business users can ask to “build a story about how the business has changed over the last month for a business review with leadership;” and in seconds, Amazon Q creates a narrative with specific insights and supporting visuals, including specific ideas of how to improve the business. Users can choose to layout the content produced by Q in an easy to share document or presentation where they can customize text, images, and themes, and use Amazon Q to rewrite and improve the text.
  • First-of-its-kind capability that helps every employee go from conversation to generative AI-powered app in seconds: Today, AWS is announcing the new Amazon Q Apps capability (in preview). Amazon Q Apps allows employees to easily and quickly create generative AI-powered apps based on their company data, without requiring any prior coding experience. With Q Apps, employees simply describe the app they want, in natural language, or they can take an existing conversation where Amazon Q Business helped them solve a problem, and with one click, Q will instantly generate an app that accomplishes their desired task that can be easily shared across their organization.

For example, creating employee onboarding plans for new recruits can be a long and laborious process. They require many hours of searching through different data stores and documents to find the appropriate content for the new employee; and often, the content is out of date or not specific enough to their role. With Q, an HR professional could simply describe they want an app that will create an onboarding plan for a new employee that utilizes the company’s existing best practices, and has an input field for employee ID that personalizes the onboarding plan to their role by drawing from internal data sources specific to their job family.  In a matter of seconds, Amazon Q Apps will build an app that can automatically generate a personalized onboarding plan tailored to the employee, their role, and the department using the latest best practices. The HR professional can then share the app with hiring managers across the company to instantly build personalized onboarding plans for their own teams.  Now, with Amazon Q Apps, business users can easily, quickly, and securely build an app based on enterprise information to improve their work productivity.

What Amazon Q customers and partners are saying

GoDaddy helps millions of entrepreneurs globally start, grow, and scale their businesses. “Amazon Q in QuickSight allows us to ask our data contextual business questions without having to constantly rely on ad-hoc dashboards. For example, now we can much more easily discover and drill into anomalies in business performance across the company,” said Ed Sarausad, senior director, Data & Analytics, at GoDaddy. “This shift not only streamlines our processes, but also elevates our analytical capabilities. What excites us most is the opportunity to unlock insights with profound, previously unasked questions. That allows us to respond more swiftly and with greater depth, enhancing our data learning journey.”

National Australia Bank is one of the largest financial institutions in Australia. “At NAB, teams across the bank are excited about how generative AI can transform our work, and we’ve found a great solution in Amazon Q Developer, a powerful generative AI-powered tool for our engineers and developers,” said Andrew Brydon, executive chief engineer at National Australia Bank. “The tool has seamlessly integrated advanced generative algorithms and tools into our development process, delivering unparalleled benefits like completing tasks faster, increasing productivity, and minimizing repetitive actions. So far, our developers have accepted 50% of the code suggestions made by Amazon Q Developer, and that number continues to increase as we scale. We look forward to seeing how Amazon Q Developer will continue to empower and inspire our engineers to upskill their technical expertise, delivering better service for customers.”

Netsmart is a leading technology provider for community-based care. “The demand for community-based care has grown exponentially, and Amazon Q Developer is helping us meet that demand by fueling our efficiency and innovation,” said Paul Snider, vice president of engineering at Netsmart. “Amazon Q Developer can transform the way our engineering team approaches research, design, and coding. Since using Amazon Q Developer, our team has seen a strong code suggestion acceptance rate of 35%. This has allowed our engineers to efficiently generate high-quality code and documentation, implement new features, which can accelerate development cycles, and significantly reduce manual effort. We are excited about the impact of Amazon Q Developer on our development processes.”

Novacomp provides a diverse range of IT products and services while specializing in Quality Assurance Automation, Software Testing services and Nearshore Outsourcing. “Modernizing applications at Novacomp has historically been a time-consuming task that is often de-prioritized against other development initiatives,” said Gerardo Arroyo, CTO of Novacomp. “Our team turned to Amazon Q Code Transformation to help upgrade a project running in Java 8 to Java 17 with over 10,000 lines of code. This is a task that would typically take an expert over two weeks to manually complete, but Amazon Q seamlessly modernized our project in a matter of minutes. Since adopting Amazon Q across our organization, we have realized a 60% decrease in average in our tech debt.”

Persistent Systems is a multi-national technology services company that builds software that drives digital transformation. “Amazon Q Apps has the potential to revolutionize the way we approach generative AI,” said Praveen Bhadada, head of generative AI at Persistent Systems. “We can now empower everyone on the team to quickly build and integrate applications with a no-code approach, using enterprise data sources while carefully aligning with existing identities, roles, and authorization levels.”

Smartsheet is an enterprise software as a service offering for collaboration and work management. “Amazon Q Business is streamlining knowledge management and accelerating employee productivity at Smartsheet,” said Bani Bedi, senior vice president, corporate development and strategy at Smartsheet. “Previously, it was too difficult for our 3,300 employees to find the information they needed across public help documents, training courses, and hundreds of all-employee Slack help channels. We have consolidated our organizational knowledge into a single AI engine to give our workforce immediate answers, significantly boosting employee productivity. Now, employees can simply tag @AskMe in any Slack channel, ask a question, and Amazon Q will instantly give them an answer. Our CEO uses Amazon Q Business to obtain answers and conduct research, getting the information that he needs without interrupting an employee’s workflow. We accomplished all of this in a couple of weeks and without writing a single line of code, using our existing identity system. Additionally, our engineering teams use Amazon Q to summarize incident statuses, identify action items, access API documentation, and troubleshoot technical issues more efficiently, so they can focus on delivering exceptional products to our customers.”

Sun Life is a leading international financial services organization. “Together with AWS, we’re leveraging generative AI to help our people work more efficiently and deliver superior digital experiences to our clients,” said Laura Money, EVP & chief information and technology innovation officer at Sun Life. “Adopting Amazon Q Apps will enable our teams to build secure and seamless solutions that create value and differentiation across our business. For example, empowering our teams with access to Amazon Q in just a few clicks will streamline the creation and sharing of applications tailored to their respective needs.”

Internal Job Cover Letter: How To Express Interest

Many job seekers applying for a new position inside the company think that their reputation is all that matters. Sure, feedback from your current supervisor is important, and it’ll definitely affect your prospects. But so is your job application, including your resume and especially your cover letter. So here are a few tips that’ll help you write a top-notch internal job cover letter

#1 Communicate Your Commitment to the Company

One of the reasons why companies often start with internal hiring is that they’re looking for a person who is well-familiar with the organization and has a nice track record within it. That’s why it’s critical that a professional cover letter for internal position clearly communicates your commitment to continuing to grow with the company.

When a hiring manager or prospective boss is reading applications for internal job opportunities, they want to see what you’ve already achieved while working at the company as well as what you’re hoping to achieve going forward. So your most important tasks are to highlight your accomplishments and express genuine dedication to the employer.

Don’t go overboard, though. Job seekers who claim that they’d like to stay with the company “for the rest of their professional life” when applying for a job risk coming across as insincere. It’s better to leave one’s long-term goals for the interview. For now, simply make sure that the recruiter or the person in charge of hiring decisions knows you’re not looking for a temporary job. A place you can also try is advertising resume writers from resumeperk 

#2 Tell Why You’re Interested in the Position

But it’s not enough to show your commitment. If you want to land an interview and hopefully get hired, include why exactly you’re interested in the position you’re applying for. Be honest, but not too honest. If the number one reason is money, don’t mention it in your cover letter. The Human Resources Team won’t appreciate it.

Instead, focus on the responsibilities the new position implies and the opportunities for professional growth it opens. Perhaps, it’s something that you’ve had a chance to try in your current role and really enjoyed (say, mentoring or assisting in talent acquisition). Then, you can write that you’ve realized you’re good at it and would like to do it more.

Alternatively, a time-tested and believable response to the question of why you’d like to change your job is that you’ve reached the ceiling in your current position. It’s not uncommon for candidates with years of work experience to feel like there’s no more room for them to grow. It’s okay to admit this.

#3 Make Sure to Explain What You Bring to the Table

Next, any internal job cover letter (or any cover letter, for that matter) should include the reasons why a candidate thinks they’re a good fit for the position. All employers are looking for competence and an impressive qualification. As an applicant, you’re supposed to assure them that you have a lot to offer.

Dedicate a paragraph or two to addressing the job requirements of the position you’re applying for and how you’re capable of meeting them. Show that you’ve read the job description thoroughly and understand how the department you’d like to work in operates. Then write about how your education and current job have prepared you for what’s (hopefully) to come.

#4 If You Think It’s Appropriate, Add a Couple of Positive Changes You’d Implement If Hired

Specificity is what a lot of cover letters lack. So if you want to impress the recruiter or even your future supervisor, make yours as specific as possible. A good way to do so is to write a paragraph or two about what you’ll do in the new role if hired. For example, if you’re applying for a position of an onboarding specialist, here are a few things you might propose in the cover letter:

  1. Beginning the onboarding process in advance by sending study materials to the new hires.
  2. Pairing every new employee with an experienced mentor for at least two weeks.
  3. Organizing informal events to organically familiarize new employees with the company culture.
  4. Involving new employees in brainstorming from the first day to make them feel welcomed and valued.

#5 Don’t Think the Job Is Yours to Lose Just Because It’s an Internal Promotion

Finally, no matter how outstanding of a track record you have within the company, don’t think that you’re guaranteed the job just because they’re looking for an internal candidate. First, you never know—a colleague of yours might submit a much stronger job application. Second, your prospective boss might be looking for a specific person, and your work experience might not be as relevant as you think.

Remember that the quality of the job application, including the cover letter, matters a lot. If you feel like you lack the writing skills to compose a winning cover letter, it might be the right step to get professional help here top resume writing service. After all, your goal is to get employed. If you need to invest in your career a bit more to achieve it, do so.

An Afterword

A cover letter is possibly the most important part of the internal job application process. For it to get you the job, you must clearly state your commitment to the company, reasons for your interest in the new position, and original ideas you’re bringing to the table. So don’t just write a few paragraphs half-heartedly, hoping your resume is enough. Make an effort.