How designers can stay relevant using artificial intelligence (AI) to their advantage

Artificial Intelligence (AI) is omnipresent, yet its vast potential often seems complex and unpredictable. Let’s delve deeper to understand AI's impact, particularly in design, and how you can harness it to your advantage.

The Impact of AI on Design

Will AI replace designers?

While AI might replace certain job roles, many economists believe its overall impact on design can be positive. AI's efficiency and productivity can create wealth and demand for new, evolved job roles, shifting labour from automated areas to non-automated ones. However, this doesn't mean there are no downsides.

The design industry, like many others, has been significantly impacted by AI. Automation in areas such as wireframing, game environment design, and photography has reduced the demand for skilled labour, leaving many designers with fewer opportunities.

Transformative AI tools in design

• Concept Design Innovations: AI tools like Midjourney, DALL-E, and Firefly generate stunning imagery from text prompts, revolutionising concept design.
• Integration in Existing Products: Photoshop with its generative fill and Illustrator with its text-to-vector graphics are two examples of how companies are adopting AI into their existing products. Both tools are game changers for designers.
• Runway ML: Using generative models, Runway ML can transform static images into dynamic video sequences.

For a comprehensive list of AI tools being introduced into the market, take a look at There’s an AI for that

Limitations of AI in design

Innovation: AI, by its nature, is limited to the data it has been fed and the tasks it has been programmed to perform. This means AI excels in efficiency and replication but struggles with innovation and breaking the norm.

The role of human ingenuity in design

• Innovation and Creativity: Innovation and creativity often require thinking beyond existing paradigms and generating ideas that have never been conceived before. AI's reliance on existing data and predefined algorithms means it can enhance and streamline creative processes but cannot truly innovate.
• Human Domain: Ideation, the process of forming new ideas, concepts, and strategies, remains a distinctly human domain. Designers and creative professionals push boundaries and explore the unknown, challenging conventions and creating breakthroughs that AI, in its current state, cannot achieve.

Designers can stay relevant by focusing on areas where human skills and intervention add significant value and leverage AI on the side to enhance their work.

The right mindset to adopt regarding AI

Innovation has always been a driving force behind progress, often leading to significant shifts in industries and societies. To understand the impact of AI, it’s helpful to look at historical examples of technological advancements and their effects.

The advent of the Loom - Early automation

In the 1980s and 1990s, the introduction of power looms in Ahmedabad's textile mills marked a period of intense competition. These automated looms greatly increased efficiency but also led to significant job losses as they reduced the need for manual labour and specialised skills.

Advantages:

• Increased efficiency: Faster production.
• Cost reduction: Lower production costs.

Disadvantages:

• Thread issues: Cannot weave thin or pure cotton without tearing.
• Job losses: Reduced need for skilled labour.

Technological advancements like power looms and AI come with benefits and drawbacks. While AI can enhance efficiency, it has limitations. Embracing AI wisely can save time and improve productivity while preserving the unique value of human skills.

The rise of new roles

My late grandfather, C.S. Shankarnarayan, worked in a textile mill in Madurai  as the manager, during this time of change. He witnessed firsthand how new technology was replacing workers. However, he adapted to the new environment by becoming part of the workforce that ensured these machines ran efficiently and fixed any issues that arose. This highlights how technological advancements can create new roles even as they render others obsolete.

The revolution in basketball

Consider the evolution of basketball. When the game was invented in 1891 at Springfield College, Massachusetts, it utilised peach baskets with bottoms. Players had to retrieve the ball using a ladder every time a basket was made. It wasn’t until 1912 that someone decided to cut out the bottom of the basket, allowing the ball to fall through. This simple yet revolutionary change eliminated the need for ladder climbers, who then found themselves out of a job.

Adapt and overcome

Great innovation often requires jumping to the next curve rather than making incremental improvements. This leap in progress can be compared to the way the telephone paved the way for the internet. Similarly, AI represents the next curve poised to revolutionise many aspects of our lives.

What does innovation look like?

• Steam engines to electric motors.
• Cutting ice blocks from frozen lakes to refrigerators.
• Hand written letters to email.
• Horse drawn ploughs to tractors.
• Wood burning stoves to electric ovens.

If you are a part of the workforce affected by AI, it’s imperative that you quickly adapt and find new roles that fit your skills before you are rendered obsolete.

Let’s understand AI better

Our understanding of AI especially as non programmers tends to be a bit hazy, and understandably so. The field of Artificial Intelligence is insanely broad, dynamic, and multidisciplinary, encompassing fields like Computer Science, Mathematics and Data Science to Neuroscience, Philosophy, and HCI (Human-Computer Interaction). With such diverse inputs, it has the capability to be used in many perspectives like Cybersecurity, Academia, and Robotics.

If we were to sit down and list the many things that are possible with AI, the only barrier to the exercise would be our imagination. Hence, it is difficult to assign a single definition to what it really means to be an AI. Though, we shall not shy away from defining it anyway, for the sake of better understanding which can be built on further. 

Programming

The base which makes it all possible. Programming is the implementation of a certain logic, by way of a language that a machine understands, to help carry out specific operations and functionality. Computer programming is how we communicate with machines in a way that makes them function how we need.

Artificial intelligence

AI is a system of varied technologies working together to do tasks that intelligent beings could do. It is the concept of a computer that can perform tasks in a complex environment without constant guidance of a user, in ways similar to an intelligent being. AI is a subset of computer science.

Machine learning

It is a subset of artificial intelligence. Computers with machine learning use algorithms to build connections and structure the data, allowing it to go from an input to an output. It has the power to be adaptive but not autonomous. The difference between AI and machine learning is that machine learning is a method to train a computer to learn from its inputs but without explicit programming for every circumstance. Machine learning helps a computer to achieve a level of artificial intelligence.

Deep learning

It is a subset of machine learning, which is a subset of AI. Deep learning uses artificial neural networks, essentially a network loosely based on the human brain. What this means is that a deep learning model has layers of “context” built into it to better “understand” the data and perform accordingly. The deep learning model also uses algorithms, but the difference is that it is based on the structure and function of the human brain, whereas machine learning uses statistical algorithms to compute and perform tasks.

Courses you can take if you’re interested in AI

• Elements of AI - Free online course designed to introduce people to the basics of artificial intelligence. The course aims to demystify AI and make it accessible to everyone, regardless of their background.
• Machine Learning by Andrew Ng - A comprehensive introduction to machine learning, covering supervised and unsupervised learning, best practices, and more.
• Deep learning specialisation - A series of courses that dive deep into neural networks, convolutional networks, sequence models, and more.
• AI foundations for everyone - An introduction to AI, its applications, and its impact on various industries.

Youtube channels to follow

• 3Blue1Brown - Focuses on maths concepts essential for machine learning and AI, explained visually.
• Sentdex - Provides tutorials on Python programming, machine learning, and deep learning using practical examples.
• Two Minute Papers - Discusses recent research papers in AI and machine learning, breaking down complex topics into understandable segments.
• StatQuest with Josh Starmer - Simplifies statistical concepts and machine learning algorithms through clear and engaging explanations.
• AI Adventures (Google Cloud Platform) - Offers tutorials and insights into AI and machine learning using Google Cloud Platform tools.
• Yannic Kilcher - Reviews the latest AI and machine learning research papers, providing in-depth analysis and explanations.

Putting it all together: An example

An AI-powered image recognition software is able to process images, identify the different elements and objects in it, and then classify them into categories. It utilises various techniques like traditional computer vision algorithms, machine learning and deep learning.

AI here is the concept of having an intelligent system.

The image recognition software has a machine learning model. This means that the software was given a database of labelled images to learn from and create patterns, say, folders of images labelled as trees, cars, butterflies, and so on. Once the software has learned the entire dataset, it can be shown completely new images and it will be able to classify them accurately. 

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The image recognition software also has a deep learning model. This model is trained to identify edges, textures, shapes, and object parts, which allows it to combine that knowledge to identify complete objects in an image. With this as a base, the deep learning model could directly be given unstructured data (a folder filled with random but labelled or even unlabelled imagery) and it would be able to classify them into categories accurately. 

Generative AI

GenAI is a type of artificial intelligence that utilises algorithms to create outputs based on a certain data set. It is trained to generate new, original content that bears some similarities to the data that it’s trained on. It can generate a wide variety of outputs, like visuals, text, video, sound, and more. It does this by learning and/or analysing data, finding connections and patterns, and then coming up with unique outputs, making the exact nature of the output often unpredictable. In a certain way, generative AI is the creative sibling out of the rest.

There’s one lovely definition of AI as mentioned in Elements of AI, though it was stated more as a joke - “Cool things that computers can't do”. Going by this statement, as soon as we find a way to do something cool with a computer, it ceases to be an AI thing. Though, if we look back in time, it kind of stands true. The technology Adobe uses in softwares like After Effects is indeed AI. When the tech first came out, it was considered revolutionary, because so many of the graphical and visual processes which were done entirely by hand, could now be done by a computer. But if you think about the current day and age, it's not as 'cool'. The definition of AI seems to be ever-evolving. 

ChatGPT

ChatGPT is an advanced conversational AI model developed by OpenAI. It is built on the GPT (Generative Pre-trained Transformer) architecture and leverages deep learning techniques to understand and generate human-like text based on the input it receives.

It has the potential to function as a personalised search engine, given its ability to process and generate information tailored to individual queries. It goes beyond traditional search engines by offering conversational interactions.

Many users find it valuable for discussing their thoughts, seeking feedback, and sharing insecurities. The example of the woman who found a cure for her son's illness after consulting numerous doctors highlights the unique and impactful ways people are leveraging ChatGPT. That does not mean it's an alternative to professional medical treatment. 

Idea generation

ChatGPT can generate a wide range of ideas based on given prompts, helping to kickstart the creative process.

Copywriting and content ideation

ChatGPT can assist in writing drafts, generating content, and editing text to ensure clarity and coherence. It can create engaging narratives, taglines, and other creative content to enhance the concept.

Placeholder content

Gone are the days of using Lorem Ipsum in designs awaiting approval. ChatGPT can generate realistic placeholder text, giving your designs a polished and complete look instead of appearing unfinished with traditional Lorem Ipsum content.

Enhanced creative exploration and brainstorming

ChatGPT won’t give you the exact answers you’re looking for, but it can be used as a starting point for your exploration. It’s especially handy when you have a creative block.

Quick understanding

Anthony Pierri and Robert Kaminski have published numerous resources on Website Messaging for Early-Stage B2B SaaS Startups. One of the resources they released is a value proposition canvas that can give you a comprehensive view of what a company does, when all the fields are filled. Download it here.

To get a detailed breakdown of a company, simply upload this PDF document into GPT4o, along with the url of the website you wish to understand, and ask it fill the PDF. Watch the magic unfold.

Midjourney

Midjourney, a generative artificial intelligence programme, took the world by storm in the year 2022. Created by San Francisco based independent research lab namely Midjourney, Inc., it provides its users the opportunity to create stunning visuals by way of simple text prompts. At least that’s where it started. Since its inception, the developers have added a variety of features and upgrades that allow for new and more innovative ways of image generation that could seep into more and more use cases. This section will cover a few of the many ways that Midjourney can transform visual design.

Ideation 

Ideation and conceptualisation, the stage where one has the highest level of freedom before having to narrow down on ideas. With the /imagine function of Midjourney, all one needs to do is concisely note down ideas and feed it into the programme. The following image is an example from our ideation for a live project.

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Apart from describing the visual, we carefully laid out our specifics for colour, contrast, texture, and treatment, to explore different kinds of look and feel. Having clarity on these points can allow visual designers to explore any kind of idea and evaluate it before taking it forward. 

Or exploring different viewpoints for spaces:

For graphic designers, its role extends beyond mere assistance, becoming a worthy catalyst for ideation, illustration, and concept art. It doesn’t end here, Midjourney has other functions like /blend, which allows users to literally blend two or more images together to come up with something absurd or amazing. Such features allow for multiple ways of idea generation. Every thought finds expression and every concept takes shape.

From Portraits to Mockups / Realistic Imagery

Often in projects, finding apt imagery of people, products or spaces is a task. It can be time consuming (hours spent finding the right image), and/or expensive (doing a photoshoot from scratch with the right tools). Though, coupling clear prompting and MidJourney can cut time and the costs, while simultaneously allowing for efficient execution.

It is important to be mindful of the words being used to describe what one wishes to generate. Mentioning the kind of lighting, the type of framing, the palette style, often, even the type of camera/film/lens helps (different tech captures and processes images differently).

With that kind of thinking and clarity in mind, you can take on any brief & imagine it:

Or simply play around:

Midjourney does end up doing quite a bit of the heavy lifting of making an image appear pretty and well composed, but unless the user precisely describes what they want, all images will end up looking similar and eventually, bland.

Using AI to enhance your process

The above is an example of how MidJourney has been used by Ray Wang, to generate (I’m against using the word illustrated. That’s just wrong.) an entire children's book. You can access the entire showcase here. Though the quality of the output is debatable, the reduction in time to create the illustrations themselves is impressive. 

One must learn to use AI tools to augment and enhance their processes. 

Let’s take the field of digital illustration as an example. Today, with the advent of AI tools like MidJourney, this landscape is evolving rapidly. Let’s delve into how the traditional illustration process compares to the modern approach enhanced by AI, and the benefits this integration brings.

The traditional illustration process

Ideation - This initial stage involves generating ideas and concepts for the illustration. Artists brainstorm, sketch, and refine their thoughts to form a clear vision.

Mood Board Creation - To set the tone and style, artists collect visual inspirations, including images, colour schemes, and artistic styles that align with the project’s vision.

Rough Sketch - Translating ideas into preliminary sketches focuses on composition, layout, and overall visual direction, laying the groundwork for the final piece.

Digital Render - Artists create a polished version of the rough sketch using digital tools, refining line work, defining shapes, and preparing for colour application.

Adding Colour - The final step involves applying colour, focusing on colour theory, shading, and creating visual depth to bring the illustration to life.

The modern illustration process

Ideation - Similar to the traditional process, generating initial ideas and concepts remains the foundation.

Using AI to Create - AI tools like MidJourney generate initial illustrations based on artist-provided prompts, producing multiple variations quickly and offering a wide range of creative possibilities.

Using AI to Improve - Artists refine and enhance the AI-generated illustrations, adjusting details, exploring different styles, and optimising the visual outcome using AI’s advanced capabilities.

Benefits of integrating AI

1. Time Efficiency - AI dramatically reduces the time required to create and refine illustrations, allowing for rapid generation of multiple variations and accelerating the creative process.
2. Faster exploration- AI enables artists to explore new styles and techniques, providing suggestions that can inspire creative directions not previously considered.

AI in Everything Design's work

Naveen Hospitals

The Naveen Hospitals website is thoughtfully crafted for affordable mental health care, tailored to individual needs. Its warm, welcoming layout guides visitors seamlessly through expert-driven psychiatric services. The brushstroke-style illustrations add a unique touch, making the experience feel accessible and comforting, much like the soothing textures of a blanket, instantly putting visitors at ease while navigating serious topics.

Ideation

Application

Lakshmigraha

The idea was to make the factory atmosphere warm and inviting, unlike the typical portrayal of non-conducive environments. Instead of a standard factory sketch, we've depicted people smiling and enjoying their work, reflecting the positive culture at Lakshmigraha. This warm human touch enhances the overall environment.

Ideation

Style finalisation

Application

Peoplebox

The ask was to create a brochure for Peoplebox to be used during an event for people management softwares. This meant the brochure had to stand out amongst a sea of competitors. How could we make a brochure that would make someone pick it up, and then most importantly, remember it later?We decided to build the concept around what an HR's life would look like if Peoplebox took care of all his troubles. Hence, we decided to show a HR on vacation, relaxing in a peaceful and dreamy landscape. We did not want it to look like typical AI-generated imagery, hence added the prompt to generate images in the style of acrylic & oil paintings, to give it more of a human quality.

Ideation

Application

Simplicontract

For SimpliContract, we had to create personas for one of the teams they cater to; the Legal Team. After research we narrowed down on physical attributes, expressions, attire, race, accessories, etc. These were then entered into the prompt to give us the perfect 'Legal Lisa'

Ideation

Application

Conclusion

The integration of AI across various design fields is transforming creative processes by enhancing efficiency and expanding possibilities. While traditional methods still hold value, AI tools like Midjourney and ChatGPT enable designers to streamline routine tasks and explore new creative directions. To stay relevant, designers should embrace AI as a complement to their skills, continuously adapting to technological advancements.

At Everything Design, we equip ourselves with the latest AI tools to stay ahead of the curve. If you’re looking to enhance your projects and stay competitive in the rapidly evolving industry, we are here to help you achieve your goals!

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