{"id":71616,"date":"2026-05-22T11:31:12","date_gmt":"2026-05-22T08:31:12","guid":{"rendered":"https:\/\/twodots.gr\/?p=71616"},"modified":"2026-05-22T11:31:12","modified_gmt":"2026-05-22T08:31:12","slug":"ta-kalytera-ergaleia-technitis-noimosynis-gia-michanikous","status":"publish","type":"post","link":"https:\/\/twodots.gr\/en\/ta-kalytera-ergaleia-technitis-noimosynis-gia-michanikous\/","title":{"rendered":"The best AI tools for engineers"},"content":{"rendered":"<style>\n.td-article-toc{border:1px solid #E5E5E5;border-radius:14px;padding:16px 18px;margin:18px 0;background:linear-gradient(180deg,#FFFFFF,#F7F8FF);} \n.td-article-toc .td-toc-title{display:flex;align-items:center;gap:10px;margin:0 0 10px 0;font-weight:700;color:#030633;} \n.td-article-toc a{color:#030633;text-decoration:none;} .td-article-toc a:hover{color:#FCA311;text-decoration:underline;} \n.td-article-toc ol{margin:0;padding-left:20px;} .td-article-toc li{margin:6px 0;} .td-article-toc li.td-toc-h3{margin-left:12px;font-size:0.95em;opacity:0.95;}\n.td-chart{border:1px solid #E5E5E5;border-radius:14px;padding:14px 16px;margin:16px 0;background:#FFFFFF;} \n.td-chart .td-chart-title{margin:0 0 4px 0;font-weight:700;color:#030633;} .td-chart .td-chart-sub{margin:0 0 10px 0;color:#4b5563;font-size:0.95em;}\n.td-chart table{width:100%;border-collapse:collapse;font-size:0.95em;} .td-chart th,.td-chart td{border-bottom:1px solid #eef2ff;padding:8px 6px;text-align:left;} .td-chart th{color:#030633;}\n.td-faq{border:1px solid #E5E5E5;border-radius:14px;padding:16px 18px;margin:18px 0;background:#FFFFFF;} .td-faq h2{margin-top:0;} \n.td-faq details{border-top:1px solid #eef2ff;padding:10px 0;} .td-faq details:first-of-type{border-top:none;} \n.td-faq summary{cursor:pointer;font-weight:700;color:#030633;} .td-faq summary::marker{color:#FCA311;} \n.td-faq p{margin:8px 0 0 0;}\n<\/style>\n<p><strong>AI tools for engineers<\/strong>: How Qual's AI tools improve engineering, QA and e-commerce workflows with driver, KPIs and secure adoption.<\/p>\n<div class=\"td-article-toc\">\n<div class=\"td-toc-title\">Contents<\/div>\n<ol>\n<li><a href=\"#ti-deichnei-to-paradeigma-tou-quals-ai-gia-tin-epomeni-genia-ergaleion\">What Qual's AI example shows for the next generation of tools<\/a><\/li>\n<li><a href=\"#giati-ta-ai-tools-ginontai-krisimi-ypodomi-gia-omades-engineering-kai-commerce\">Why AI tools are becoming critical infrastructure for engineering and commerce teams<\/a><\/li>\n<li><a href=\"#pou-metafrazetai-i-axia-se-e-commerce-operations\">Where value translates into e-commerce operations<\/a><\/li>\n<li><a href=\"#step-by-step-odigos-yiothetisis-ai-tools-se-mia-e-commerce-epicheirisi\">Step-by-Step guide to adopting AI tools in an e-commerce business<\/a><\/li>\n<li class=\"td-toc-h3\"><a href=\"#kritiria-epilogis-kai-governance\">Selection criteria and governance<\/a><\/li>\n<li><a href=\"#kpis-riska-kai-i-epomeni-kinisi-gia-e-commerce-owners\">KPIs, risks and the next move for e-commerce owners<\/a><\/li>\n<li><a href=\"#piges\">Sources<\/a><\/li>\n<li class=\"td-toc-h3\"><a href=\"#pos-epireazoun-ta-ai-tools-tin-paragogikotita-se-e-commerce\">How do AI tools affect productivity in e-commerce?;<\/a><\/li>\n<li class=\"td-toc-h3\"><a href=\"#poia-einai-ta-pleonektimata-tis-chrisis-ai-sta-e-commerce-operations\">What are the advantages of using AI in e-commerce operations?;<\/a><\/li>\n<li class=\"td-toc-h3\"><a href=\"#giati-ta-ai-tools-einai-krisimi-ypodomi-gia-e-commerce\">Why are AI tools critical infrastructure for e-commerce?;<\/a><\/li>\n<li class=\"td-toc-h3\"><a href=\"#poia-einai-ta-vasika-kritiria-epilogis-ai-ergaleion-gia-e-commerce\">What are the key criteria for selecting AI tools for e-commerce?;<\/a><\/li>\n<li class=\"td-toc-h3\"><a href=\"#pos-borei-ena-e-commerce-katastima-na-yiothetisei-apotelesmatika-ai-ergaleia\">How can an e-commerce store effectively adopt AI tools?;<\/a><\/li>\n<li class=\"td-toc-h3\"><a href=\"#poioi-einai-oi-kindynoi-apo-tin-anexelegkti-chrisi-ai-ergaleion\">What are the risks of uncontrolled use of AI tools?;<\/a><\/li>\n<li class=\"td-toc-h3\"><a href=\"#poia-einai-ta-simantikotera-kpis-gia-tin-axiologisi-ai-ergaleion-se-e-commerce\">What are the most important KPIs for evaluating AI tools in e-commerce?;<\/a><\/li>\n<\/ol>\n<\/div>\n<h2 id=\"ti-deichnei-to-paradeigma-tou-quals-ai-gia-tin-epomeni-genia-ergaleion\">What Qual's AI example shows for the next generation of tools<\/h2>\n<p>The DesignNews article on Qual's AI illuminates a shift that no longer affects just engineering labs, but any business that relies on complex processes, documentation, specifications, quality and speed of execution. AI tools are no longer presented as generic chatbots that answer questions, but as specialized systems that get into the workflow, understand technical context, help analyze requirements, and reduce time wasted in repetitive cognitive work. For an e-commerce owner, this message is more practical than it seems: e-commerce has an \u2019engineering\u201c side too, from the storefront and ERP interfaces, to catalog management, pre-campaign QA, product compliance, descriptions, return policies, logistics and customer experience.<\/p>\n<p>The essence behind Qual's AI paradigm is that AI is starting to move from the level of inspiration to the level of operational precision. An AI tool that helps engineers is not enough to \u201cwrite beautifully\u201d. It needs to connect data, capture assumptions, support decisions, reduce errors and enhance traceability. This is exactly the difference between a simple text generation AI tool and a solution that can support workflow automation in a serious business environment. In e-commerce, the same logic translates into tools that can analyze technical tickets, compare product specifications, identify deficiencies in catalog data, suggest improvements to landing pages, and help marketing, development and operations teams work with a common vision.<\/p>\n<p>The global adoption of AI shows that this shift is not theoretical. According to McKinsey, AI use in organisations rose from 55% in 2023 to 72% in 2024, while generative AI use increased from 33% to 65% in the same timeframe. The graph below illustrates why AI tools should be treated as a strategic infrastructure rather than a passing trend.<\/p>\n<figure class=\"td-chart\">\n<p class=\"td-chart-title\">Adoption of AI and Generative AI in Organisations<\/p>\n<p class=\"td-chart-sub\">Source: McKinsey, The State of AI in Early 2024<\/p>\n<table>\n<thead>\n<tr>\n<th>Year<\/th>\n<th>Organisations using AI<\/th>\n<th>Organizations using generative AI<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>2023<\/td>\n<td>55%<\/td>\n<td>33%<\/td>\n<\/tr>\n<tr>\n<td>2024<\/td>\n<td>72%<\/td>\n<td>65%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n<h2 id=\"giati-ta-ai-tools-ginontai-krisimi-ypodomi-gia-omades-engineering-kai-commerce\">Why AI tools are becoming critical infrastructure for engineering and commerce teams<\/h2>\n<p>The most important conclusion for e-commerce professionals and owners is not that \u201cAI does everything\u201d, but that the right AI tools can compress the time between information and decision. To an engineering team, this can mean faster specification reading, automatic first draft creation for test plans or better requirements management. In an online store, it can mean faster diagnosis of a problem at checkout, better sorting of thousands of SKUs, more consistent product descriptions, quicker compatibility checks between marketplaces and CMS, or more immediate documentation of changes before a major release.<\/p>\n<p>The interesting thing about AI tools for engineers is that they often act as \u201cdocumentation partners\u201d. This has huge implications for businesses as they grow. While an e-shop is on a small scale, many decisions are based on the memory of the founder, developer or marketing manager. But when products, campaigns, channels, shipping countries and integrations grow, the memory of the team is not enough. You need a system that understands what has changed, what is affected and what is the next safe step. That's where AI requirements management is not a technical luxury, but a way to reduce operational risk.<\/p>\n<p>Productivity is the first point that becomes visible. In a controlled GitHub study of Copilot, developers using the tool completed a specific task in about 71 minutes, while the control group took about 161 minutes. The difference doesn't mean that every task will speed up to the same degree, but it shows how big the impact can be when an AI code assistant is integrated into a clean task, with clear criteria and human oversight.<\/p>\n<figure class=\"td-chart\">\n<p class=\"td-chart-title\">Coding Task Completion Time with and without AI<\/p>\n<p class=\"td-chart-sub\">Source: GitHub Copilot Research, controlled experiment<\/p>\n<table>\n<thead>\n<tr>\n<th>Year<\/th>\n<th>Time of completion<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Without AI assistant<\/td>\n<td>161 minutes<\/td>\n<\/tr>\n<tr>\n<td>With GitHub Copilot<\/td>\n<td>71 minutes<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n<p>For an e-commerce owner, the lesson is not to blindly buy any AI code assistant. The lesson is to look for cases where there is a high volume of repetitive work, clear business value and the ability to control the outcome. If the shop has frequent releases, custom features, bugs in integrations or a need for faster QA, then AI tools can reduce the time from ticket to fix. Similarly, if the content team manages a large catalog, AI tools can speed up drafts, translations, metadata and structured product attributes, as long as there is ultimate human control.<\/p>\n<h2 id=\"pou-metafrazetai-i-axia-se-e-commerce-operations\">Where value translates into e-commerce operations<\/h2>\n<p>The practical value of AI for e-commerce lies primarily in five areas: operational speed, data quality, better customer experience, reduced support costs and faster product development. In operational speed, AI can read tickets and suggest priorities, summarize customer feedback, create internal briefs and help teams not start from a blank page every time. In data quality, it can identify duplicate records, inconsistencies in product attributes, incorrect categorizations or descriptions that don't match the commercial strategy. In customer experience, it can support personalization, intelligent search, recommended products and better scripts for customer support.<\/p>\n<p>But the digital transformation side requires discipline. Many companies start with enthusiasm, try three or four AI tools, but don't define who uses them, with what data, for what purpose and with what success metrics. The result is scattered use with no real ROI. The example of engineering tools, such as the one described by DesignNews, is a reminder that value occurs when AI is tied to a specific workflow: requirements, analysis, documentation, execution, testing, and improvement. The same should be true in e-commerce. It's not enough to say \u201cwe put AI in.\u201d We need to know if catalogue errors were reduced, ticket resolution time was reduced, conversion rate was improved, landing page production was accelerated or cost per order was reduced.<\/p>\n<p>The trend among technology professionals confirms that AI use is not peripheral. According to the Stack Overflow Developer Survey, the percentage of developers using or planning to use AI tools in the development process increased from 70% in 2023 to 76% in 2024. This has immediate relevance for e-commerce businesses working with developers or agencies: productivity, speed of delivery and quality of collaboration will be increasingly influenced by how maturely AI tools are utilized.<\/p>\n<figure class=\"td-chart\">\n<p class=\"td-chart-title\">Developers Using or Planning to Use AI Tools<\/p>\n<p class=\"td-chart-sub\">Source: Stack Overflow Developer Survey 2023 and 2024<\/p>\n<table>\n<thead>\n<tr>\n<th>Year<\/th>\n<th>Use or intention to use AI tools<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>2023<\/td>\n<td>70%<\/td>\n<\/tr>\n<tr>\n<td>2024<\/td>\n<td>76%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n<h2 id=\"step-by-step-odigos-yiothetisis-ai-tools-se-mia-e-commerce-epicheirisi\">Step-by-Step guide to adopting AI tools in an e-commerce business<\/h2>\n<p>Proper adoption does not start with buying software, but with mapping out the friction points. A practical guide for e-commerce owners can start with the following steps. First, list the repetitive tasks that consume time without requiring high strategic judgment: enriching product descriptions, answering FAQs, tagging, internal reports, checking product feeds, summarizing reviews, creating briefs for developers and QA checklists. Second, classify these tasks based on volume, cost of error, and human reviewability. A high-volume, low-risk task, such as initial grouping reviews, is ideal for pilot implementation. A high-risk task, such as changing prices or legal terms, requires tighter governance.<\/p>\n<p>Third, choose a use case with a clean KPI. For example, \u201creduce time to create product descriptions by 40% without quality drop\u201d, \u201creduce tickets involving wrong product information\u201d, \u201cfaster QA preparation before seasonal campaign\u201d or \u201creduce time to write technical brief for new integration\u201d. Fourth, create a small pilot environment with real data, but without exposing sensitive customer information, trade secrets or personal data without proper protection. Fifth, define roles: who gives prompts, who evaluates, who approves, who records errors, and who decides whether the pilot scales.<\/p>\n<p>Sixth, build a library of prompts and rules. Prompt engineering is not a magical skill, but operational standardization. A good prompt should define role, objective, input data, constraints, style, output format and control criteria. For example, an e-commerce brand might ask the AI to generate a product description with a specific length, forbidden words, tone of voice, mandatory technical attributes and SEO fields. Seventh, measure results on a weekly basis. Don't limit yourself to the feeling that it \u201cworks faster.\u201d Measure time, cost, cost, percentage of fixes, impact on conversion, impact on organic traffic and impact on customer support.<\/p>\n<p>Eighth, connect AI tools to processes and not just people. If usage is left to the most \u201cinquisitive\u201d employee, the business does not gain true capability. It needs a playbook, training and shared standards. A mature AI for business setup includes a data policy, list of approved tools, rules for personal data, review process and a clear framework for when the AI output is considered just a draft and when it can go into production. Such a framework helps to avoid errors, excessive expectations and shadow tool use by the team.<\/p>\n<p>The fourth criterion is embeddability. The best tools do not force the team to constantly copy and paste information. They link to existing systems or at least output results in a format that can be used. The fifth is performance measurement. A tool for AI quality assurance should help measure how many errors were detected before they reached the customer. A tool for ecommerce automation should show time savings, cost reductions or production speed increases. A tool for content operations should demonstrate that it doesn't just produce more content, but better, more consistent and more useful content.<\/p>\n<h2 id=\"kpis-riska-kai-i-epomeni-kinisi-gia-e-commerce-owners\">KPIs, risks and the next move for e-commerce owners<\/h2>\n<p>AI tools can increase speed, but speed without control can create new problems. The key risks are inaccuracies, over-reliance on unsourced answers, data leakage, inconsistency in brand voice and producing content that doesn't really help the customer. This requires a combination of technology, processes and human judgment. AI needs to act as an accelerator for the team, not as an unchecked replacement. Especially in markets where products have technical specifications, regulations or high value, the final review by an expert remains essential.<\/p>\n<p>The most useful KPIs for an e-commerce business are specific: time to produce content per SKU, rate of corrections after AI draft, time to resolve technical tickets, number of bugs detected before release, time to prepare campaign pages, rate of returns due to incorrect product information, organic clicks from optimized pages, conversion rate on pages where AI-assisted optimization was applied and cost of service per order. If the business doesn't measure these metrics before adoption, it won't be able to prove afterwards whether the AI tools created value.<\/p>\n<p>The most practical next step is a 30-day pilot. Choose a limited but important use case, such as improving 200 product pages, sorting customer reviews, creating a QA checklist for checkout changes or automating internal briefs for developers. Set a baseline, measure time and quality, compare results and decide if it's worth scaling up. This approach is safer than uncritical adoption and more productive than waiting. The market is already moving toward specialized, workflow-based AI tools; companies that leverage them with the right strategy will have an advantage not because they \u201chave AI\u201d but because they will execute faster, with better control and clearer knowledge of their processes.<\/p>\n<p>The conclusion from Qual's AI and from the evolution of AI tools for engineers in general is clear: the real value lies in the application to critical workflows. For e-commerce, this means that AI needs to move from experiments to the operating model. When AI tools are linked to real data, clear goals, human oversight and measurable KPIs, they can become a driver of growth, quality and competitive differentiation.<\/p>\n<h2 id=\"piges\">Sources<\/h2>\n<p><a href=\"https:\/\/www.designnews.com\/artificial-intelligence\/ai-tools-for-engineers-quals-ai\" target=\"_blank\" rel=\"noopener\">DesignNews: AI Tools for Engineers: Qual's AI<\/a><\/p>\n<p><a href=\"https:\/\/www.mckinsey.com\/capabilities\/quantumblack\/our-insights\/the-state-of-ai\" target=\"_blank\" rel=\"noopener\">McKinsey: The State of AI in Early 2024<\/a><\/p>\n<p><a href=\"https:\/\/github.blog\/news-insights\/research\/research-quantifying-github-copilots-impact-on-developer-productivity-and-happiness\/\" target=\"_blank\" rel=\"noopener\">GitHub Research: Quantifying GitHub Copilot's Impact on Developer Productivity<\/a><\/p>\n<p><a href=\"https:\/\/survey.stackoverflow.co\/2024\/ai\" target=\"_blank\" rel=\"noopener\">Stack Overflow Developer Survey 2024: AI<\/a><\/p>\n<p><a href=\"https:\/\/survey.stackoverflow.co\/2023\/#ai\" target=\"_blank\" rel=\"noopener\">Stack Overflow Developer Survey 2023: AI<\/a><\/p>\n<div class=\"td-faq\">\n<h2>Frequently Asked Questions (FAQs)<\/h2>\n<details>\n<summary>Selection criteria and governance<\/summary>\n<p>To choose the right AI tools, consider five key criteria. The first is subject matter expertise. A generic chatbot may be useful for insights, but a business with a complex catalog or technical products needs a solution that can handle structured data, attributes, categorization rules and possibly integration with PIM, ERP or CMS. The second is transparency. The team needs to be able to check where a proposal comes from, especially when it involves technical specifications or commercial decisions. The third is data security. Ask where the data is stored, whether it is used for model training, who has access and what contracts cover the processing.<\/p>\n<\/details>\n<details>\n<summary>How do AI tools affect productivity in e-commerce?;<\/summary>\n<p>AI tools can increase productivity by reducing time on repetitive tasks such as creating product descriptions and solving technical problems. They also improve data quality and customer experience while reducing support costs.<\/p>\n<\/details>\n<details>\n<summary>What are the advantages of using AI in e-commerce operations?;<\/summary>\n<p>AI tools boost operational speed, improve data quality and deliver a better customer experience. They also reduce support costs and accelerate product development.<\/p>\n<\/details>\n<details>\n<summary>Why are AI tools critical infrastructure for e-commerce?;<\/summary>\n<p>AI tools offer a strategic infrastructure that links information to decision making, reducing time and errors in complex processes. This is vital for managing large lists and improving workflows.<\/p>\n<\/details>\n<details>\n<summary>What are the key criteria for selecting AI tools for e-commerce?;<\/summary>\n<p>Choose AI tools that specialize in your field, offer transparency and data security, and integrate easily with existing systems. It's also important that their performance can be measured to prove their value.<\/p>\n<\/details>\n<details>\n<summary>How can an e-commerce store effectively adopt AI tools?;<\/summary>\n<p>Start by mapping friction points and select low-risk repetitive tasks for piloting. Set clear KPIs, create a library of prompts and measure the results to decide if scaling is worth it.<\/p>\n<\/details>\n<details>\n<summary>What are the risks of uncontrolled use of AI tools?;<\/summary>\n<p>Uncontrolled use of AI can lead to inaccuracies, data leakage and inconsistency in brand voice. A combination of technology and human judgment is necessary for safe and effective use.<\/p>\n<\/details>\n<details>\n<summary>What are the most important KPIs for evaluating AI tools in e-commerce?;<\/summary>\n<p>Important KPIs include content production time, post-AI draft correction rate, and conversion rate. These help measure the true value that AI tools provide.<\/p>\n<\/details>\n<\/div>\n<h2>Want to implement AI tools safely?;<\/h2>\n<p>TWO DOTS undertakes end-to-end implementation: from <a href=\"https:\/\/twodots.gr\/aftomatismoi-epicheiriseon-ai\/\">business automation &amp; AI<\/a> and links to <a href=\"https:\/\/twodots.gr\/erp-epicheirisiaka-logismika\/\">ERP<\/a>, until <a href=\"https:\/\/twodots.gr\/kataskevi-eshop\/\">e-shop construction<\/a> and <a href=\"https:\/\/twodots.gr\/digital-marketing-seo\/\">Digital Marketing &amp; SEO<\/a>.<\/p>","protected":false},"excerpt":{"rendered":"<p>The DesignNews article on Qual's AI highlights the evolution of AI tools from generic chatbots to specialized systems integrated into business processes. This shift is also impacting e-commerce, where AI tools are improving data analysis, product management and customer experience. Strategic adoption of AI, with a focus on reducing repetitive work and boosting productivity, is critical to business success.<\/p>","protected":false},"author":1,"featured_media":71615,"comment_status":"open","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_gspb_post_css":"","footnotes":""},"categories":[199],"tags":[7261,6507,7232,9064,7204],"class_list":["post-71616","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-techniti-noimosyni","tag-ai-tools","tag-digital-transformation","tag-e-commerce-automation","tag-engineering-automation","tag-generative-ai"],"blocksy_meta":[],"_links":{"self":[{"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/posts\/71616","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/comments?post=71616"}],"version-history":[{"count":0,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/posts\/71616\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/media\/71615"}],"wp:attachment":[{"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/media?parent=71616"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/categories?post=71616"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/tags?post=71616"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}