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Oct 10 2024
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AI’s Impact on Software Development: How Artificial Intelligence is Transforming the Industry cover

AI’s Impact on Software Development: How Artificial Intelligence is Transforming the Industry

By AI, chatgpt, Innovation, Product

Artificial intelligence is revolutionizing software development by automating repetitive tasks, enhancing testing accuracy, and streamlining debugging processes. This transformation allows developers to focus on creative solutions and strategic challenges. As AI reshapes the industry, adaptability and continuous learning become crucial for staying ahead in an AI-driven future.

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May 02 2023
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AI in UX: The Next Frontier in Design Innovation cover

AI in UX: The Next Frontier in Design Innovation

By AI, Digital Transformation, Experience Design, Innovation, Personalization, UX

Photograph of AI robots
Remember how just a couple of years ago we were frequently discouraged by SIRI not being able to understand what we were saying and constantly answering the wrong question? Our cars had trouble with voice recognition and more often than not were calling the wrong person. Those of us who have accents had an even harder time talking to our devices and hoping to be understood. How many jokes have you heard about autocorrect? It is amazing to see how quickly technology improved in just a few years. Clearly, AI is already being used in a variety of ways to improve UX today.

AI applications in our daily lives

Every one of us experiences the effects of artificial intelligence in our everyday life.

  • Companies like Netflix use AI to recommend movies and TV shows based on your viewing history.
  • Amazon Alexa, Siri, and Google Assistant are using AI to control smart devices, send messages, set reminders, and provide information, creating a more seamless user experience.
  • A lot of companies use AI-powered chatbots to provide customer support, answer questions, and provide personalized recommendations, enhancing the user experience and reducing the workload on human support teams.
  • UserTesting uses AI to analyze user feedback and provide insights to UX designers.

We all can agree that as technology continues to advance, AI will revolutionize UX design in a number of ways. Here are some of the most obvious changes we can expect to see:

  1. Improved personalization.
  2. Better automation
  3. Enhanced predictive analytics
  4. Increased variety and quality of conversational interfaces
  5. Enhanced accessibility
  6. Improved testing and feedback

But like with everything in life, it is important to know not only the strengths and benefits of the new technology but also the potential dangers.

Let’s take a deeper look at each one of those items.

Personalization

Advanced data analysis can help UX researchers to analyze user data more effectively and accurately. It can provide insights that can lead to more personalized experiences. However, just like in market research, collecting more data doesn’t necessarily help with understanding its meaning. Designers and researchers may be tempted to rely too heavily on data instead of considering user feedback and intuition.

AI can help navigate the complexity of real-time personalization by quickly analyzing user behavior and preferences. The latter will allow to better adapt to the needs of individual users. Personalization, in its turn, can help to further improve chatbots and voice assistants. However, some users may be uncomfortable with the level of personalization that AI can provide. Hence, designers should be ready to face reluctance to accept the new technology solutions on the customer side.

Automation

There is a number of daunting and tedious tasks that UX designers do on an everyday basis. AI can help speed up design processes. By generating design variations such as layout, typography, and color selection, designers will be able to quickly test different assumptions. On top of that, design areas that can benefit from AI extend to design systems and much beyond.

Image of colored gear wheels

At the same time, designers relying too much on automation can cause a loss of creativity. It can also shift expectations on how long the design process should take and promote the so-common “anyone can do it” attitude.

We also should not forget that automated systems require upkeep and maintenance. So designers must invest time and resources into maintaining and improving their automation tools. Always keep in mind, automation should be something that complements, rather than replaces creativity and thought.

Enhanced accessibility

One of the interesting areas where AI can make a significant difference is accessibility. Accessibility refers to the practice of designing products and services that can be used by people with disabilities, such as visual or hearing impairments. Companies should start looking into AI to help them with 508 compliance.

AI-powered voice assistants, automatic captioning, image recognition, and natural language processing (NLP) are critical elements of enabling people with disabilities to work seamlessly and productively. Voice commands can provide an accessible experience for people with visual or motor impairments. Automatically generated captions for videos and other media can make them accessible for people with hearing impairments. Besides, image analysis and description can provide users with visual impairments with the much-needed ability to understand visual content. And finally, chatbots and other conversational interfaces help people who need assistance with cognitive or language processing.

The use of AI can help developers of those systems generate code to provide much-needed features. In this case, we can view developers as users of intelligence-powered tools that increase their productivity.

Improved testing and feedback

It is hard to overestimate the importance of testing and feedback in any design process. AI can improve designers’ efficiency and effectiveness by automating testing processes, analyzing user feedback, identifying patterns and trends, and A/B testing.

Predictive analytics and NLP can be used to anticipate user behavior, extract important insights, and better understand user needs.

However, it is critical for designers to understand the limitations of AI and incorporate human feedback and intuition into the design process, balancing the insights provided by AI with the creativity and empathy of human designers.

Predictive analytics

Predictive analytics uses machine learning algorithms to analyze user data and predict future user behavior. Everything we’ve talked about in this article heavily relies on predictive analytics. AI helps with the analysis of large volumes of user data, making real-time predictions, optimization of user experiences, and testing multiple design variations.

Image of a screen that shows data charts

Integration of AI tools into existing applications

Yes, AI can help designers do their work, but let’s not forget about the enormous help that AI can provide for our users in their day-to-day work.

Incorporating generative AI into email applications and text editors can help people to communicate more effectively by providing them with initial structures of emails, PowerPoint presentations, and documentation.

Bringing AI into internal corporate portals can save time for thousands of employees during the onboarding process, or when seeking for right people or procedures within the organization.

Thousands of existing applications currently heavily rely on people using other applications or search engines (Google, YouTube, etc.) to provide additional assistance with their products. Imagine how powerful and productive those products could become if by using AI they could seamlessly bring this external content into their products.

Dangers of AI

We spoke a lot about the multiple positive effects that AI can have on design processes, but let’s not forget that there are multiple areas in which using AI (especially in its current state) can be rather dangerous.

AI algorithms are not perfect, and designers as well as their managers must be aware of the limitations of the technology they are using. The correct interpretation of user feedback is pivotal for a designer. However, the use of AI does not always guarantee accuracy.

The accuracy and reliability of predictive analytics depend not only on the data quantity used to train the AI model but also on the data quality. Designers may start relying too heavily on data from AI-powered testing and feedback tools, potentially overlooking important subjective experiences and feedback.

In addition, AI algorithms may reinforce existing biases in data, leading to biased feedback and potentially misleading design decisions. AI also doesn’t have empathy which is necessary to truly understand user needs and preferences.

When using AI tools, designers need to verify that data is collected in an ethical and responsible way, protecting user privacy and ensuring that the system doesn’t have negative impacts on users or society.

Final thoughts on AI in UX

Overall, there is a lot of complexity associated with the use of AI in the design process, and it is important to find the right balance between possibilities and practicality. Designers should also beware of the limitations of emerging tools and take precautions to prevent misleading design outcomes.

Nov 06 2020
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No-code vs. Custom Code: What is a Better Fit for User-centered Design?

No-code vs. Custom Code: What is a Better Fit for User-centered Design?

By AI, Application Development, Digital Transformation, Innovation, User Experience, User Interface, UX

Ever-evolving software technologies and no-code or low-code tools are transforming a traditional way of creating digital products. In the last few years, creating software can be done faster, simpler, and with a lower barrier of entry than ever before. One of the reasons is that user-centered design has come to the forefront of most software development processes. At the same time, the need for the software creator to code is being replaced with drag-and-drop interfaces, freeing up space for creativity, rapid prototyping, and continuous testing.

But does this trend mean that custom coding will completely vanish in the next few years? Or, can these two approaches exist in parallel, complementing each other?

This article will explain the concept of no-code and low-code development in the context of building user-centered design. Ideally, you’ll find out whether you’ll benefit more from a low-code development approach, or if custom coding is what you need for your projects.

What “low-code” and “no-code” actually mean

As the name suggests, low-code or no-code development is a practice of building digital products with little or no coding. It’s made possible by platforms allowing users to create software solutions by just dragging and dropping necessary elements, or features, into the relevant fields. The main goal of these platforms isn’t limited to visualizing product designers’ ideas like in Sketch or InVision. They let you build an actual interface with functioning features on it, as opposed to creating a UX/UI mockup.

The low-code/no-code approach reflects recent changes in the development process and business requirements. Today, the main focus is shifted from the product functionality to the product presentation.

development process
Image credit: zapier.com

Modern businesses understand that the strong orientation towards users has become a ‘gold standard’ in the digital world. Naturally, as technology develops, design decisions play a more critical role than it did before. These factors create a demand for quicker prototyping and frequent user feedback collection. The birth and rise of low-code/no-code development is a technology response to this global trend.

Benefits of no-code development

office people

The potential benefits of the low-code/no-code development approach goes far beyond speed and simplicity. This practice can significantly reduce the gap from the ideation and execution stages of app development – drastically changing the way businesses embrace innovation. Here are the key advantages of using low-code/no-code development platforms.

Rapid delivery for the supreme time-to-value

Rapid delivery is probably the most obvious benefit of the low/no-code approach. With low-code/no-code automation tools, you can build a web or mobile application really quickly, even if you can’t code. The accelerated development speed can help startups that plan to launch a product or service in a highly competitive market gain a considerable competitive advantage.

For mature enterprises, rapid delivery is also beneficial as it allows for improved flexibility and adjustability. Besides, the fast time to market enabled by low-code/no-code solutions can help businesses of any size iterate more often and create products with truly user-centered design.

Driving force behind digital transformation

Low-code and no-code tools facilitate a digital transformation process and lower the barrier of entry to innovation. In practice, it allows business professionals with no or minimum technical background to bring their ideas to life without the necessity to wait until developers will do the work. This practice is called civil development, and it helps enterprises resolve IT challenges faster and more effectively.

For example, an HR or marketing department may need quick internal transformations to improve its efficiency. In these scenarios, low-code can be a great solution as it doesn’t require a lot of time and money from an enterprise.

Additionally, low-code and no-code development create more favorable conditions for building user-centered design for business applications. It is because the people who need the software solutions are the ones who actually build them, as opposed to delegating the task to the IT department.

Simplified prototyping and usability testing

To create an outstanding UX design, a development team should test a product on its potential users before the release. The more iterations take place, the higher the chances are for a successful product launch. Basically, this is the foundation of most agile development methodologies.

With low-code/no-code tools, programmers can quickly and easily build a product and test its every core feature. As a result, they can generate enough knowledge to tailor a user experience to the needs and wants of a target audience. Besides, low-code/no-code development enables the implementation of the Lean UX approach. This Lean UX method prioritizes rapid iterations and puts an even greater focus on collecting user feedback.

Benefits of custom coding

coding

Low-code/no-code options cannot fully replace custom development. Writing code from scratch also has many advantages that are essential for solving certain business challenges. Let’s take a closer look at them.

Uniqueness and specialized interactivity

With low-code and no-code development, you can create a good design. However, this approach won’t allow you to build a unique solution. In other words, if you need an application with specialized interactivity, custom coding will be a better fit for you.

This slightly more traditional approach to product development usually requires more resources, but it also gives you a higher level of freedom and expertise. Basically, developers can implement any product idea you have. Whereas, if you select low-code/no-code development, your choice of features and UX design elements will be limited to options offered by a tool vendor.

Complex functionality and state-of-the-art technologies

Complex functionality and sophisticated data models can only be implemented with custom coding. It means that low-code/no-code solutions won’t be of help for businesses that need an enterprise-wide application. Similarly, when it comes to making use of innovative technologies such as AI, virtual and augmented reality, blockchain, etc, there is no alternative to custom code development.

Low-code/no-code vs custom code: what to choose for your business

Both approaches can benefit most businesses —  each addressing different needs. However, in order to help you decide what type of development to select for a specific project here are some hints that will help.

Choose low-code/no-code development for:

  • simple tools for automating simple business operations
  • basic solutions for eliminating bottlenecks in specific work-flows
  • new digital products that require extensive and/or regular user feedback to be built properly
  • new digital products that have to be released quickly (e.g., to outrun the competition)
  • idea validation, if you’re not sure whether people need certain functionality (ideal for startups)

Choose custom code for:

  • complex feature-rich solutions
  • products based on AI, VR, AR, or any other innovative technology
  • long-term development projects with uncertain requirements
  • unique products that cannot be developed with low-code/no-code tools
  • larger digital products that will reach a large user-base to ensure solidity at scale

However, it is possible for you to use both approaches in one project. For example, you may be able to build a high-fidelity prototype with low-code/no-code tools to test key assumptions and then proceed with custom coding to create a full-fledged product.

Conclusion

In the no-code vs. custom code battle, there is no single winner. Low-code/no-code development can be a great solution for building simple applications, usability testing,  prototyping, and experimenting. The wide adoption of this practice can drive innovation across different industries and cultivate creativity in product development.

However, the low-code/no-code approach cannot compete when it comes to the scale and unique features possible through custom development. Writing code remains vital when it comes to the development of unique and complex software solutions.

Want to develop a software product but not sure what approach to choose? Contact us!

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