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How to Enhance UX/UI with Artificial Intelligence and Machine Learning

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How to Enhance UX/UI with Artificial Intelligence and Machine Learning


Artificial Intelligence is widely used in various industries to automate routine tasks and increase the productivity and efficiency of business strategies. One more area where AI is becoming extremely useful is user experience and user interface (UX/UI) design. While AI can save designers time and perform routine tasks, such as image cropping, designers can focus on more complex tasks that require a high level of creativity. However, this is not the only advantage of Artificial Intelligence. ML models get “smarter” and can drive better UI/UX design. On that note, let’s dig deeper.

The Role of AI in UX/UI

Before we look at the importance of artificial intelligence in design, let’s briefly recap what UX/UI design is. User experience design (UX) is the creation of a product or service that meets users’ needs and expectations. How does the user interact with the product? How does the user feel after the interaction? These and other questions are key to UX design.

UX designers’ responsibilities are to analyze important product elements, create product schematics and prototypes, conduct user testing, and more. The primary goal of a UX designer is to make a product or service convenient, enjoyable, and accessible to the end user.

User interface design involves creating the interface’s appearance and functionality. UI designers strive to make the design clear, accessible, and inclusive, which helps the user navigate the interface. UI designers are also responsible for choosing the correct color palette, fonts, layout, and other elements. Overall, the work of a UX/UI designer requires creativity and flexibility in many tasks. So, there are certain tasks that AI can help designers with:

  • Automate time-consuming manual work (image resizing);
  • Perform localization of designs through AI-powered translation;
  • Segment audiences and provide the right product with an interface;
  • Give insight into what elements users interact with the most and which require the most attention;
  • Provide system consistency between users and products by using wireframing and prototyping tools.

Thus, AI helps designers improve the user experience and reduces the need for human labor in various ways (data analysis, creation of design documentation). The interaction between AI and designers leads to increased productivity and efficiency, as well as increased customer satisfaction, which affects brand loyalty.

How does Artificial Intelligence enhance UI/UX design?

Now that you have an overview of the value of AI in design let’s shift the focus to specific examples. Here are some important use cases of how AI can improve UX/UI design.

Automation of routine tasks

Often a designer’s job involves routine tasks that can be time-consuming. Image cropping, resizing, and color correction of photos are some examples of how designers spend their time. Designers can’t automate simple tasks in Photoshop because the tasks require human curation and the ability to make quick decisions. What if artificial intelligence could do the job instead of designers?

Artificial Intelligence can relieve designers of time-consuming tasks, thereby increasing efficiency. There are many solutions offered by AI, such as Adobe Scene Stitch technology, which identifies patterns in an image, helping designers correct, edit, or reimagine a particular scene. In this way, optimizing repetitive, routine tasks with AI can free up designers’ time to think about other strategic product design decisions.

Human chatbots

In the digital world, chatbots are a great way for UX/UI designers to improve the customer experience and attract new audiences. AI-based chatbots improve user experience using natural language processing. Machine-learning-based chatbots are programmed to self-learn as they become familiar with new dialogues and words. In fact, if a chatbot receives unfamiliar voice or text dialogues, the number and accuracy of their responses increase. AI helps make interactions with UX/UI chatbots more comfortable and human-like, improving the user experience.

Efficient data analysis

Machine learning does, thanks to advances in technology and most of the data collection. But that doesn’t mean a company will need fewer analytics specialists. More analysts can perform a more accurate and in-depth analysis of user interactions with the brand by using the conduct of UI/UX testing, such as A/B tests or usability tests, to increase user engagement with their products. With AI, designers can track many critical UX metrics, such as:

  • Pages visited;
  • Session time;
  • Products viewed;
  • Bounce rates;
  • Exit pages.

Collecting a huge amount of data allows designers to create a user-centered design. User-centered design, UCD, is a design process that focuses on the needs (behaviors, values, expectations) of users at every stage of brand interaction. Artificial intelligence models collect data about the target audience and identify user requirements and goals from different channels. In addition, AI tools allow designers to experiment with new ideas and concepts.

Information Architecture (IA)

In the world of UX design, users use digital products that are well-structured and easy to use. This is not unintentional but the result of a good Information Architecture. Information Architecture helps organize and structure information or content, including text, photos, and videos, in a digital product according to user requirements. For example, when designers create apps and websites, they plan the screen so that the user can easily find the information they want and navigate between screens.

Designers use information architecture to plan the navigation system to make users comfortable using the product. AI can help an AI model better interpret data, find patterns, and ultimately provide a user-centered approach to design. Without a good information structure, a machine learning model does not succeed because there will be no data to learn. Thus, combining AI and information architecture helps organizations focus on customer requirements by providing more structured content and an easy-to-understand interface.

Accessibility of the prototyping tools and wireframing

Communicating the value of an idea to those interested before designers create a product or design can be difficult. That’s why designers use rapid and advanced prototyping tools, which are used to evaluate a new product or design for further improvement. Designers only need a few sketches so that the artificial intelligence system can quickly transfer ideas from sketches to real life.

In this way, AI-powered prototyping tools help designers:

  • Provide the intent of the ultimate design;
  • Provide a user-centric design;
  • Protect design solutions to customer feedback;
  • Save time and money by making changes early on.

However, designers can use AI not only as a tool to turn raw drawings into highly accurate prototypes but also as a tool to explore wireframe ideas. User experience designers often use wireframes to provide clients with how a user interface will look and work in advance if it’s realized. By using artificial intelligence to create an interface, designers can set design direction, and machines learn possible design choices and then suggest the best solutions. Thus, prototyping tools’ and wireframing simplify the UX design process, reduce time, and allow designers to focus on the more important aspects of the project.

Can artificial intelligence take over the work of UX/UI design?

Artificial Intelligence helps UX/UI designers create and improve user-centric products, saving time and energy. While AI can learn from human experience, improve and produce better results, the ability to bring in creative alternatives, machines still can’t. Therefore, the lion’s share of product design work still falls on the shoulders of designers.

Understanding human needs and applying them to design is the key to success for UX/UI designers. Will AI replace designers? Share in the comments your personal thoughts about it.

Featured Image Credit: Picjumbocom; Pexels; Thank you!

Anastasia Grishina

Anastasia is a content creator at SoftTeco. She likes creating informative and interesting content about cutting-edge technologies. Anastasia is also a frequent author of articles on various platforms on technical topics.

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Fintech Kennek raises $12.5M seed round to digitize lending

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Google eyed for $2 billion Anthropic deal after major Amazon play


London-based fintech startup Kennek has raised $12.5 million in seed funding to expand its lending operating system.

According to an Oct. 10 tech.eu report, the round was led by HV Capital and included participation from Dutch Founders Fund, AlbionVC, FFVC, Plug & Play Ventures, and Syndicate One. Kennek offers software-as-a-service tools to help non-bank lenders streamline their operations using open banking, open finance, and payments.

The platform aims to automate time-consuming manual tasks and consolidate fragmented data to simplify lending. Xavier De Pauw, founder of Kennek said:

“Until kennek, lenders had to devote countless hours to menial operational tasks and deal with jumbled and hard-coded data – which makes every other part of lending a headache. As former lenders ourselves, we lived and breathed these frustrations, and built kennek to make them a thing of the past.”

The company said the latest funding round was oversubscribed and closed quickly despite the challenging fundraising environment. The new capital will be used to expand Kennek’s engineering team and strengthen its market position in the UK while exploring expansion into other European markets. Barbod Namini, Partner at lead investor HV Capital, commented on the investment:

“Kennek has developed an ambitious and genuinely unique proposition which we think can be the foundation of the entire alternative lending space. […] It is a complicated market and a solution that brings together all information and stakeholders onto a single platform is highly compelling for both lenders & the ecosystem as a whole.”

The fintech lending space has grown rapidly in recent years, but many lenders still rely on legacy systems and manual processes that limit efficiency and scalability. Kennek aims to leverage open banking and data integration to provide lenders with a more streamlined, automated lending experience.

The seed funding will allow the London-based startup to continue developing its platform and expanding its team to meet demand from non-bank lenders looking to digitize operations. Kennek’s focus on the UK and Europe also comes amid rising adoption of open banking and open finance in the regions.

Featured Image Credit: Photo from Kennek.io; Thank you!

Radek Zielinski

Radek Zielinski is an experienced technology and financial journalist with a passion for cybersecurity and futurology.

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Fortune 500’s race for generative AI breakthroughs

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Deanna Ritchie


As excitement around generative AI grows, Fortune 500 companies, including Goldman Sachs, are carefully examining the possible applications of this technology. A recent survey of U.S. executives indicated that 60% believe generative AI will substantially impact their businesses in the long term. However, they anticipate a one to two-year timeframe before implementing their initial solutions. This optimism stems from the potential of generative AI to revolutionize various aspects of businesses, from enhancing customer experiences to optimizing internal processes. In the short term, companies will likely focus on pilot projects and experimentation, gradually integrating generative AI into their operations as they witness its positive influence on efficiency and profitability.

Goldman Sachs’ Cautious Approach to Implementing Generative AI

In a recent interview, Goldman Sachs CIO Marco Argenti revealed that the firm has not yet implemented any generative AI use cases. Instead, the company focuses on experimentation and setting high standards before adopting the technology. Argenti recognized the desire for outcomes in areas like developer and operational efficiency but emphasized ensuring precision before putting experimental AI use cases into production.

According to Argenti, striking the right balance between driving innovation and maintaining accuracy is crucial for successfully integrating generative AI within the firm. Goldman Sachs intends to continue exploring this emerging technology’s potential benefits and applications while diligently assessing risks to ensure it meets the company’s stringent quality standards.

One possible application for Goldman Sachs is in software development, where the company has observed a 20-40% productivity increase during its trials. The goal is for 1,000 developers to utilize generative AI tools by year’s end. However, Argenti emphasized that a well-defined expectation of return on investment is necessary before fully integrating generative AI into production.

To achieve this, the company plans to implement a systematic and strategic approach to adopting generative AI, ensuring that it complements and enhances the skills of its developers. Additionally, Goldman Sachs intends to evaluate the long-term impact of generative AI on their software development processes and the overall quality of the applications being developed.

Goldman Sachs’ approach to AI implementation goes beyond merely executing models. The firm has created a platform encompassing technical, legal, and compliance assessments to filter out improper content and keep track of all interactions. This comprehensive system ensures seamless integration of artificial intelligence in operations while adhering to regulatory standards and maintaining client confidentiality. Moreover, the platform continuously improves and adapts its algorithms, allowing Goldman Sachs to stay at the forefront of technology and offer its clients the most efficient and secure services.

Featured Image Credit: Photo by Google DeepMind; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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UK seizes web3 opportunity simplifying crypto regulations

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Deanna Ritchie


As Web3 companies increasingly consider leaving the United States due to regulatory ambiguity, the United Kingdom must simplify its cryptocurrency regulations to attract these businesses. The conservative think tank Policy Exchange recently released a report detailing ten suggestions for improving Web3 regulation in the country. Among the recommendations are reducing liability for token holders in decentralized autonomous organizations (DAOs) and encouraging the Financial Conduct Authority (FCA) to adopt alternative Know Your Customer (KYC) methodologies, such as digital identities and blockchain analytics tools. These suggestions aim to position the UK as a hub for Web3 innovation and attract blockchain-based businesses looking for a more conducive regulatory environment.

Streamlining Cryptocurrency Regulations for Innovation

To make it easier for emerging Web3 companies to navigate existing legal frameworks and contribute to the UK’s digital economy growth, the government must streamline cryptocurrency regulations and adopt forward-looking approaches. By making the regulatory landscape clear and straightforward, the UK can create an environment that fosters innovation, growth, and competitiveness in the global fintech industry.

The Policy Exchange report also recommends not weakening self-hosted wallets or treating proof-of-stake (PoS) services as financial services. This approach aims to protect the fundamental principles of decentralization and user autonomy while strongly emphasizing security and regulatory compliance. By doing so, the UK can nurture an environment that encourages innovation and the continued growth of blockchain technology.

Despite recent strict measures by UK authorities, such as His Majesty’s Treasury and the FCA, toward the digital assets sector, the proposed changes in the Policy Exchange report strive to make the UK a more attractive location for Web3 enterprises. By adopting these suggestions, the UK can demonstrate its commitment to fostering innovation in the rapidly evolving blockchain and cryptocurrency industries while ensuring a robust and transparent regulatory environment.

The ongoing uncertainty surrounding cryptocurrency regulations in various countries has prompted Web3 companies to explore alternative jurisdictions with more precise legal frameworks. As the United States grapples with regulatory ambiguity, the United Kingdom can position itself as a hub for Web3 innovation by simplifying and streamlining its cryptocurrency regulations.

Featured Image Credit: Photo by Jonathan Borba; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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