How AI is Transforming Creative Processes

Data analytics, software development, and marketing have experienced immense growth since the advent of AI, accepting AI tools to improve the quality of their outputs as well as the speed with which they deliver.  

On the other hand, the reception of artificial intelligence among creatives is still very much in the balance. While many artists and creators believe that AI tools are a superb addition to the creative process, many view artificial intelligence as competition for originality and quality. 

Actually, it is not, since AI can't be regarded as creative simply because it can create art. Creativity remains a largely human attribute, and in this blog, we will explain how creatives should see AI as a boost to their creativity, a partner for brainstorming in the creative process rather than a competition.  

The Intersection of AI and Human Creativity 

The concept of artificial intelligence has been around since the 1950s. Computer scientists designed software programs that could tinker with lines, creating different geometric shapes and patterns.  

The algorithms started with simple shapes, especially 2-D polygons, but they advanced pretty quickly, and by the mid-70s, computer-aided design (CAD) tools were already quite popular in the design world. CAD algorithms quickly gained global acceptance, as designers could now use software to create more intricate designs than simply geometric shapes.  

Scientists developed AI techniques such as neural networks to allow computers to create more sophisticated art forms. One of the foremost examples we have is Harold Cohen and his work on the AARON program, an AI tool that could create original artwork to rival humans. Soon, AARON’s works were exhibited in galleries globally, sparking conversation on AI creativity and its applications in art and design. 

Today, we have various generative AI algorithms that can create designs thanks to the extensive database that they access. From designs, artificial intelligence has expanded into other creative sectors–written content, music, and video production–leveraging its immense data sources to analyze patterns in the art world and make predictive solutions for brands and creatives alike. 

For example, a clothing brand looking to stay ahead of the fashion industry could use generative AI with its design team to get the best of human and AI. In this case, the AI is not in competition with the designers for quality output; instead, the AI can make predictions on future fashion trends by accessing historical data on trending designs.  

AI-driven predictions like this will keep the brand ahead of the fashion curve and support the design team in thinking outside conventional fashion.  

The Power of Predictive Solutions 

AI tools fall into two broad classes; generative and predictive. Both forms of artificial intelligence crawl through massive amounts of data across databases, but they process such data differently and for different use cases.  

While generative AI software uses the information to create new content–designs, text, pictures, videos, predictive AI analyzes the data to create future trends.  

In the example explained above, the clothing brand uses predictive AI to analyze past fashion trends to help the designers glimpse likely future cloth design favorites. Predictive performance is only achievable when the AI uses the following techniques to collate, analyze, and present data: 

Deep learning 

All AI uses deep learning to get used to relevant historical data. In the case of predictive AI, the more quality data they can access, the more accurate and insightful their predictive solutions become. Machine learning is quite similar to deep learning in that it allows creatives to feed the AI with relevant data so that the algorithm can spot patterns and make better decisions. Dragonfly AI has used biological cues to train the predictive algorithm which relies on a bottom-up processing approach to mimic human responses to visual stimuli offering a highly accurate prediction algorithm.  

Data analysis 

AI can't make predictions without some data analysis to start with. The algorithm collects, organizes, and analyzes data to enhance its insights and make better predictions.  

Pattern recognition 

With pattern recognition, your predictive AI connects the dots in past events to arrive at a possible forecast for the future. With their intensive data analytics, AI tools are more likely to sense patterns where humans cannot detect them, thus speeding up the decision-making process.  

Forecast techniques 

Which enables the AI to make relevant predictions based on the already analyzed data.  

Already, you can decipher the benefits of using AI for predictive analytics. With predictive AI, brands, creatives, and businesses can: 

Achieve higher efficiencies 

Analytics takes a long time, and comprises several repetitive tasks that could make sorting through more prone to errors. With AI tools, you get a thorough analytical experience at reduced error rates.  

Wide range of creative options 

Because predictive AI–all AI, really–can go through enormous amounts of data in a short period, they can generate more creative predictions. With several trends and leads at their disposal, creatives have a wide range of options for future direction. 

Cost-effective 

The point of saving time and money has always been a strong argument for AI generally. The ability of predictive AI to analyze vast data banks for forecasting ensures it saves the creatives the additional cost of more personnel to get through the same work in a similar timeframe. 

More effective forecasts 

With a predictive AI in place, your brand has better-focused predictive solutions to dominate future market trends, regardless of the sector.  

H2: Showcasing the Potential with Predictive Analytics 

Many people argue that predictive AI tools are not useful in creative fields because they rely heavily on existing data to provide predictive insights. Generative AI has pushed the barriers of creativity by generating unconventional content, and now, many creatives incline towards generative rather than predictive AI.  

However, the best results come out when creatives use generative AI tools with predictive algorithms. The major limitation of generative AI is that it could create impractical and illogical outputs, but predictive AI tools solve that rather easily.  

Already, brands are employing predictive AI to identify possible future problems before they occur. For example, Volvo detects faulty motor parts in its vehicles using predictive algorithms. The AI analyzes feeds from the vehicle's sensors and predicts when a part could start malfunctioning.  

In business and marketing, AI predictions have helped manage stock, track consumer favorites, and recommend accurate options for customers. Amazon has leaned on its AI resources to suggest products to its clients based on their browsing and transaction history, thus increasing the likelihood of conversions.  

Walmart has also successfully streamlined its business processes with the predictive behavior of AI tools, from stock inventory to predicting likely future customer demands. 

In copywriting, predictive AI can reveal which marketing copy, ad, or poster will appeal better to clients. After creating several copies of a single ad with generative AI, you can run them through a predictive tool to choose which ads will bring in the most conversions. Since predictive AI knows which phrases, images, and videos clients will best connect with, it can be used to create ads and copies with maximum clicks and impressions.  

The use of predictive AI influences decision-making in the following ways: 

Data-based forecasting 

With predictive AI tools in creative departments, you can be sure of fact-based predictions rather than human intuition. The final decision on the brand's direction lies with humans, but valuable AI predictions go a long way to influence such decisions. 

Proactive approach 

Problem-solving occurs at every stage of content creation and creativity. Insights from an efficient AI tool allow human personnel to take a proactive approach to solving problems, as the predictive behavior will spot such issues before they occur to reduce the risks involved. 

Precision 

Fact-based forecasts beat subjective opinions every time. Predictive AI programs offer more accurate insights due to their reliance on data, thus reducing the error risks.  

Strategic planning 

Businesses stand to gain a lot from incorporating predictive AI in their decision-making. The insights from such algorithms offer a competitive advantage in the market since they are always accurate and fact-based. 

AI Predictions as the Creative Partner 

As we stated earlier, combining AI tools with human efforts is a perfect way to get the best out of your design team. Unlike humans, AI algorithms don't get bored with repetitive tasks; they sort through them, learning and connecting the dots that could be easily missed by humans.  

On the other hand, AI algorithms are simply idea boxes for brainstorming. Any AI algorithm–generative or predictive–is only as good as the data it learns from. Apart from that, they lack much of the creativity that humans boast of and can only enhance the overall creative output when they are properly trained using relevant data and humans interpret their findings accurately.  

With the increasing global adoption of artificial intelligence, there are still several ethical issues to be considered in AI usage. 

• Lack of transparency and accuracy, since it could be difficult to identify the sources that an AI tool derives its content from. 
• Copyright infringement: AI tools crawl through vast amounts of databases to create their content. The databases contain copyrighted material, which could cause legal issues for content creators.
• Content bias could arise in AI development, especially during deep or machine learning. In cases where the content used to train the algorithms is skewed or biased on a subject, the AI will eventually perpetuate such bias. 

Preparing for a Future with AI-Assisted Creativity 

The gradual acceptance of artificial intelligence is inevitable. At any rate, we are only going to see more of the software algorithms in the creative landscape soon. Consequently, it's best for brands and creatives if they upgrade their creative processes to support an AI-human synergy, rather than oppose AI tools or see them as a threat. 

For instance, with generative AI, a design team can input prompts for creative, out-of-the-box designs that could spark revolutionary changes in various sectors. As stated earlier, the gen AI tools will function as idea boxes from where human creatives can draw inspiration for fresh content across sectors.  

Predictive AI will come in for decision-making, especially after market research. The tools will sift through the gen AI output and select content with the best appeal and highest market potential to keep the brand ahead of others.  

AI tools can also be used to automate tasks like data analysis and client/consumer monitoring. The software algorithms are better at gathering, collating, and analyzing data without errors, making them more efficient for the overall creative process. This also leaves the human personnel to focus on the more creative aspects of the task and decision-making.  

Predictive solutions will also impact business decisions and marketing campaigns as outlined above. AI predictions have found use cases in many tasks, from fault predictions/detection to industry trend forecasts. In the long run, brands and businesses will come to rely on such predictive behavior to guide their content choices. 

Conclusion  

Essentially, no AI tool is here to replace human input. Besides the ethical concerns, there is no substitute for the human mind, and artificial intelligence will only ever be a tool to boost creativity. Synergizing AI inputs with human creativity will undoubtedly lead to high-quality, innovative content that will bring about increased user engagement and satisfaction. 

Nowadays, there are various AI algorithm suites designed for specific creatives. Dragonfly AI is your best shot at taking your business's creative side to the next level. Our Studio leverages predictive solutions and analytics to predict what each of your customers sees first on your creative and boosts your conversions across channels.  

Book a 15-minute demo with one of our specialists from Dragonfly AI today, and optimize your brand at scale!