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Forbes
4 days ago
- Business
- Forbes
How To Get Your Business Featured In Generative AI Results In 2025
Manish Mittal is the Founder & CEO of OpenSource Technologies, providing AI-driven software consulting and custom web & mobile app solutions The explosion in the use of generative AI has radically changed how people search for information on the internet. ChatGPT is a great example of how a bulk of online search behaviors has gradually shifted to generative AI, with the tool hitting over 400 million weekly active users globally as of February 2025. OpenAI has set a new target for over a billion users by the end of the year after it hit a milestone of more than 5 billion monthly visits. These facts point to the increasing relevance of generative AI and why businesses need to start optimizing for AI platforms alongside traditional search engines. Practical SEO Strategies For Generative AI Traffic The SEO landscape is changing fast with the rise of AI-powered platforms like ChatGPT, Perplexity and Bing Copilot Search providing answers to users' queries. Businesses should understand the need to modify their SEO approach for AI. To help your company stay ahead of the curve, here are seven tried-and-true tactics for increasing visibility in generative AI tools. The type of content you publish has to be authoritative and clear. You should avoid speculation and include appropriate structure in your content, and here is how to do that. Write 'answer-first' content. Ensure that the first paragraph of your content carries a direct answer to the topic you are discussing. Ensure that you include FAQs, glossaries and structured service and product pages written in clear, authoritative language. Focus on user intent (i.e., what a human would actually ask an AI, such as "What is the best CRM for small businesses?" or "How can I choose a secure e-commerce platform?"). Finally, for better structure, use H1/H2 headers, bullet points and internal linking. This also improves readability. High-quality backlinks have an effect on what AI recommends. How do you go about this? Look for authority sites, respected industry publications and possible press announcements on reputable news outlets within your niche to publish in and link back to your piece. You might also consider platforms like Medium and Substack. Make use of forums like Reddit, Stack Overflow, Quora or more niche forums. Provide contextual and relevant solutions. Directories are also a good place to get backlinks. Sites with good and quality backlinks are more likely to be selected by AI for its responses. Schema markup helps AI and search engines better view and interpret your content for its potential audience. To implement schema markup across your site, you can use a site like to add: • FAQ schema for commonly asked questions • Product schema with ratings and pricing • Organization schema with your business info • Review schema to showcase customer testimonials Then you can validate with Google's Rich Results Test and make updates via Google Tag Manager or hard-coded schema. Beyond their training data, it is easier for generative AI to pull information from platforms used to train them. The best way to take advantage of this is to post valuable content on sites like Reddit, Quora, YouTube, GitHub and Medium. Providing value should be your goal, not just an opportunity to embed a link. For example, you should aim to answer industry-specific questions, share how-to videos or walk-throughs, or comment on trending topics in your niche. When you do this often, AI will recognize your website alongside its established sources and will readily use your website's resources when relevant queries come up. Although generative AI doesn't target keywords in the SEO sense of things, it can identify common search patterns and brand mentions. You can optimize your website by targeting common search queries that align with your services. For example: • "Business Name + custom API development company" • "Best AI software company in New Jersey" Focus on long-tail, location-specific and pain-point-driven keywords. Be sure to regularly update your page metadata, titles and H1 tags to reflect these terms. High authority directories are one of the places AI platforms get their data from. There are a few ways to get on these third-party directories. Make sure your profiles are updated and consistent across the more popular directories, including Crunchbase, G2, Capterra, Clutch, Yelp or BBB. Include keywords, services, location, awards, reviews and links to your website. Generative AI likes new data, and what better way to organize new data than through original research, providing insights and organizing relevant industry statistics. You can achieve this by conducting actual surveys or case studies and publishing usage data. You can also share benchmarks, market insights or industry reports and add relevant graphs, charts and references to support your claims. Platform-Specific Tips To improve visibility in ChatGPT responses, make sure your website is easy to crawl and index. Being featured or referenced on reputable industry blogs and media outlets can also increase your chances of being included in AI-generated answers. Additionally, offering downloadable resources or tools, such as calculators, templates or white papers, can help your content stand out, as these are frequently highlighted. For Perplexity, focus on creating content that is both clear and authoritative, as the platform cites its sources directly. Use page titles that align with common search queries, such as "Best [Service] in [City] 2025," to increase relevance. Organize your content with clear headings and concise, well-structured answers. Conclusion Although generative AI search is just gaining traction, there are ways to get a piece of the pie early. Once you are able to create relevant, high-quality content, structure the content appropriately, get reputable backlinks and stay active across AI-loved platforms, you'll make it easier for AI to spot and pull up your content in its search queries. This is just the beginning. Getting in now gives your business a chance to capture traffic fast. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Forbes
20-05-2025
- Business
- Forbes
AI Vs. Developers: A Future Of Collaboration, Not Competition
Manish Mittal is the Founder & CEO of OpenSource Technologies, providing AI-driven software consulting and custom web & mobile app solutions AI is moving closer and closer to the realm of science fiction, especially in software development. Generative AI (GenAI) tools that started simply by predicting the next sequence have developed fast and are conducting impressive development tasks. This begs the question: Can AI replace developers? If you are looking for a straight yes or no answer, it's still too difficult to call, but some nuances should be considered. One of the key functions of AI is to increase the efficiency of users, and it's doing just that for developers. Recent Capgemini research found that "organizations using generative AI have seen a 7% to 18% productivity improvement in software engineering." Likewise, IDC forecasts that by 2027, 60% of net-new applications that leverage GenAI will be developed with AI code assistants or low-code tools involved in the process. Clearly, AI is accelerating how we build, but it's not replacing the why, what or how behind great software. Here's why developers are still indispensable: While GenAI tools are great at patterns, they struggle with context and niche-specific knowledge that developers are armed with. For software development, this includes: • Business-specific logic. • Legacy systems. • User pain points and product vision. • Regulatory requirements (e.g., HIPAA in healthcare). This is a common consensus among most developers. Stack Overflow found that only 43% of developers trust AI outputs, and nearly half believe that "AI is bad or very bad at handling complex tasks." This gives credence to the idea that AI is an accelerator and not yet a decision-maker. The importance of cybersecurity compliance and measures cannot be overstated. This becomes more true when many AI models today hallucinate insecure codes that could cause long-term damage. A CSET study found that 48% of AI-generated code (download required) contained insecure code. According to a Venafi report cited by ITPro, 92% of security leaders are concerned about how developers are using AI. Most companies—especially those in industries with strict regulations, such as healthcare, government agencies or finance—will continue to require constant human intervention, not only machine-generated suggestions. There is a lot that goes into the process of writing code, including: • Participating in product discussions. • Refining user stories. • Conducting peer code reviews. • Collaborating with other professionals (i.e., QA, DevOps, design and product management). While AI has made significant strides in its output recently, it cannot yet replicate soft skills like creativity, leadership and empathy, which are vital for efficient collaboration. AI is doing an excellent job in its code and content-generation departments, but all of these codes are gathered from existing databases. AI cannot think for itself, invent new ideas from scratch, empathize or respond to authority. True innovation, such as designing a brand new UX framework or identifying and providing solutions to novel problems, still falls squarely within the range of human ingenuity. The concept of evolving or being left behind is still quite real. AI is not necessarily chasing developers off the market, but helping the more creative and adaptive developers evolve in their roles. Job titles like prompt engineer, human-in-the-loop reviewer, AI-augmented engineer or machine teaching specialist have begun to pop up. AI now handles the more basic tasks like: • Generating documentation. • Translating legacy code. • Writing test cases. • Repetitive scripting. • Boilerplate code. This shift in tasks allows developers to focus on: • Designing architecture. • Making product decisions. • Ensuring code quality and maintainability. • Managing integrations with third-party APIs. • Leading cross-functional initiatives. Gartner research cited by EY predicts that by 2025, 70% of new applications will be built using low-code/no-code platforms. This has caused anxiety among junior developers or those working on create, read, update and delete (CRUD)-heavy apps. But here's the truth: These tools reduce the barrier to building apps, especially for non-developers, but that is where their usefulness stops. In building more complex projects, as others have pointed out, an experienced developer will still be needed. AI is poised to replace developers who are unwilling to master their craft and stay relevant, but those who harness its advantages will enjoy its multiplier effect. The type of developers who will step into this new AI-filled world are those who understand code, AI and systems and can exploit them to their advantage. The same goes for teams and organizations. AI is here to stay, and only those who can adapt to mastering it will move into the future with confidence. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Forbes
26-03-2025
- Business
- Forbes
GenAI: Optimizing Product Management, Search And Customer Experience
Manish Mittal is the Founder & CEO of OpenSource Technologies, providing AI-driven software consulting and custom web & mobile app solutions Online shopping has consistently grown since after Covid-19, and more customers are shopping online than ever before. E-commerce accounts for 20% of global retail sales and generates $4.12 trillion in revenue globally. This space is changing, and generative AI is one of the major contributors to this change. According to Precedence Research, e-commerce AI efforts will generate upwards of $54 billion by 2032. There are a lot of unique ways generative AI is transforming e-commerce operations across the internet, including: One of the most relevant uses for generative AI in e-commerce is content generation. Beyond random content generation, generative AI is used by e-commerce brands to generate content that is tailored to individual clients. These contents include marketing emails, website copy, product descriptions and more. Generative AI's capabilities have even extended further, allowing for customization of some product designs and virtual try-ons. Combining both these capabilities, customers can now fully experience a form of practical testing of these products to meet their needs before making a buying decision. Generative AI is also having a big influence on customer service. Chatbots driven by AI have progressed from basic answer generators to advanced virtual assistants that can handle intricate customer inquiries. Generative AI allows these chatbots to comprehend the conversational environment and deliver responses that are more precise and tailored to the user's needs. Consequently, consumers get better service all around thanks to faster and more informative support agents. Beyond the customer-facing aspects of e-commerce businesses, generative AI is also finding applications in improving security for e-commerce platforms. AI-generated fraud detection algorithms are growing increasingly advanced, allowing for more efficient identification and prevention of fraudulent transactions. AI systems can better analyze transaction patterns to identify suspicious actions as they happen and take appropriate actions to safeguard e-commerce platforms and customers. Since generative AI can help brands deal with large amounts of data, they are often used in segmenting audiences and can accurately aid businesses in forecasting the next actions of various customers based on their previous data. With this understanding, brands can position content to address particular pain points of customers at certain points in their buying process and also improve the whole buying process for these customers. This data can also help businesses target specific customer demographics with customized experiences that fit their profiles rather than offering generic solutions to all customers. Major fashion brands like H&M use generative AI to afford customers customized clothes design functionalities, which puts their customers at the center of the buying process, highly increasing the chances of a customer making a purchase. This is another key way generative AI is being used on e-commerce platforms. The provision of a visual search that allows users to take pictures of samples of the products they are looking for, with AI helping to make the connections and provide accurate results, is a game changer for many e-commerce platforms. Services like OpenSource Technologies take this AI function a step further with processes like its natural language processing capabilities. This allows AI to better identify and interpret common search phrases like '3-legged table' to give more accurate results. Furthermore, there is the improved contextual feature allowing AI to correct spelling mistakes, and identify synonyms for certain searches improving results for users. To cap its visual search function, OpenSource Technologies provides a voice search optimization function that allows hands-free searches with great accuracy. The benefits of adding generative AI tools to e-commerce operations are easily derived from their multiple use cases. These use cases by various businesses across the globe do not always work out smoothly, and these challenges sometimes require out-of-the-box solutions. Some of these challenges include: Generally, older legacy customer relationship management (CRM), enterprise resource planning (ERP), inventory management systems and other existing software for e-commerce operations may not integrate well with new AI tools that can improve their operations. Finding possible bottlenecks and thoroughly mapping the current systems are necessary for seamless integration. Making sure that data flows smoothly between platforms is essential for keeping operations running. Working with IT professionals and AI experts to create custom solutions that connect old and new systems can be a viable way forward in resolving this challenge. Generative AI tools and models are often trained on a wide range of data, and the quality of the data they are trained on determines the quality of their output. A problem could arise when building custom tools for specific e-commerce operations. The quality of data available to e-commerce platforms will determine the quality of their output and the success of deploying the AI tool. The easy fix is to get high-quality input, but doing so may involve obtaining difficult-to-get permits, which would increase expenses and time. The improvement of AI technologies has been rapid from the very first popularized generative AI models to the likes of DeepSeek, GPT4. Ordinarily, this comes with its advantages but it also has its drawbacks. With each new iteration of AI models, some tools built on previous models become obsolete. Keeping up with these changes can be expensive and time-consuming, but missing out on these changes can leave profitable e-commerce operations struggling for relevance. This is a case where a modern solution comes with its problems. Although AI adoption has been widespread among businesses and e-commerce platforms, many customers are still skeptical about its safety, privacy and accuracy. This is a hurdle that can only be overcome with time and education for customers. Generative AI is changing e-commerce operations in real time for numerous brands. When employed strategically, it can improve customer experience, inventory management and decision-making. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
