AI in Product Development – Examples and Benefits 

For years, successful brands have shared common features such as having a strong customer focus, superior industry knowledge, and the ability to think ‘outside of the box’.  

In today’s digital world, we are seeing more companies add artificial intelligence to this success factor list. There are many reasons for its adaptation — quicker decision-making, process optimization, improving customer service, cost reduction, and ramping up product development processes, among others. The integration of AI and product development can transform the way companies innovate and bring products to market.

In this article, we will explain the benefits and examples of AI in product development to aid you in determining whether AI is the ideal approach for assisting your team. 

What is the role of AI in product development? What is it used for?  

AI in product development goes far beyond being another ‘add-on’ to speed up processes. It’s worth knowing that the sole fact of implementing AI doesn’t automatically mean you’re going to achieve the desired results. In order to use it to reap the full benefits, you must embrace a data-strategy-first mindset. The goal here is to thoroughly brainstorm, ideate, and strategize how exactly the AI solution is going to support your business.   

By following a well-thought-out approach to AI, you can do more than simply ensure that your company follows the times and keeps up with market trends. It’s about leveraging these tech advancements to stay one step ahead of your competitors through the ability to develop products faster. 

While it may make sense to follow what other major brands are doing, there is not one sure-fire approach that is best for everyone. So, be aware of common mistakes of AI adoption. A proper strategy is key to implementing the best AI systems for your business.  

Integration of AI in the product development process — how can it help? 

Integrating AI into the product development lifecycle can support many aspects of a business. From architecture to manufacturing, AI has something for every industry. Below we discuss seven areas that are being improved by AI integrations today:  

Project management  

AI tools can follow a project from beginning to end and accurately measure progress along the way. Further, such tools are currently used for business analysis automation, estimating resource allocation, and making predictions for budget requirements.  

By eliminating some of the time-consuming, burdensome tasks that would otherwise be completed by a team member or project manager, focus can be placed on critical points of a project, and team members can complete tasks specific to their expertise.  

For example, AI is able to estimate story point capabilities for individual team members based on prior sprint performances. It assesses the overall averages and length of time taken up by similar tasks.  

Software project requirements gathering 

Gathering requirements manually can be somewhat risky for project members. Namely, it opens doors for mistakes and missing out on pertinent information. To combat this issue, AI algorithms gather and transform user stories into functional requirements to help predict the specifications needed in future products. Not only are mistakes being reduced, but companies are also seeing up to a 50% reduction in the time it takes to gather project requirements.  

Product development strategy  

To maintain efficiency in projects, implementing a proper product development strategy is essential. AI can act as a support system for experienced specialists looking to incorporate post-launch user feedback and suggestions into a product.  

AI in product development can also be used to compare similar products and offer suggestions based on current social media trends.  

Analyzing Customer Data and Market Trends

As AI tools play a crucial role in analyzing customer data and conducting market research, you can leverage them to analyze market trends (and even to predict future trends) to better adapt your product to the actual needs of its target audience. Such a data-driven approach ensures that your product will be not only relevant but also competitive in the market. Additionally, AI can uncover hidden patterns and insights, enabling more strategic decisions and innovative product enhancements.

Software frontend design 

User experience and user interface (UX/UI) designers are seeing the positive impact of AI product development processes as well. AI especially helps UI/UX designers with automating tasks and speeding up prototype development. 

Furthermore, AI techniques and algorithms allow designers to monitor how their audience interacts with a product and make suggestions on how to customize apps based on user activities.

AI-powered software product security 

AI in product development offers added security by analyzing large amounts of data and making risk-focused predictions based on any atypical findings.  

Authentication methods such as facial recognition and biometric scanning allow companies to essentially stay ahead of hackers, malware, and unknown viruses by quickly alerting them when any potential threats arise.  

Thanks to these techniques, companies are saving tons of money by addressing threats before they cause any harm to their system(s). 

Software architecture design 

AI product development tools assist specialists with recognizing user requirements and developing designs tailored to those requirements. By incorporating AI and machine learning algorithms, these tools can adapt and refine designs based on evolving user needs and data patterns.

It’s important to note that AI tools should not be viewed as a replacement for specialists. Rather, they function as wingman who helps guide them through their processes more efficiently.  

AI in quality assurance 

Quality assurance is an important step for any product development process as it focuses on complying with set standards and market requirements. 

AI product development processes assist testers with analyzing code, locating any errors, and making proper corrections. This significantly reduces the time spent in the product testing phase. 

The emergence of AI in manufacturing is perhaps one of the best examples of AI-related quality assurance. Co-founder of Google Brain and Coursera, Andrew Ng, recently offered his thoughts on the topic saying, “AI will perform manufacturing, quality control, shorten design time, and reduce materials waste, improve production reuse, perform predictive maintenance, and more.”

Leveraging Natural Language Processing in Product Development

Natural language processing (NLP) is a powerful AI technology with big benefits for product development. It helps machines understand and respond to human language, improving various stages of product creation. For example, during requirements gathering, NLP tools can analyze customer feedback from surveys, social media, and support tickets to find common themes and needs. This helps shape product features that really matter to users.

Additionally, NLP, combined with generative AI, can enhance customer service. NLP-powered chatbots and virtual assistants can understand and respond to customer questions in real time, making interactions smoother. This frees up your team to focus on more complex tasks instead of routine inquiries.

NLP isn’t just for understanding and generating text; it also plays a key role in sentiment analysis. By looking at customer sentiments, NLP helps businesses see how their products are viewed in the market, leading to smarter decisions and better products. With NLP and generative AI, you can create products that keep meeting your customers’ evolving needs.

Benefits of AI in product development  

AI product development processes and machine learning tools involve using algorithms to generate immediate decisions for products. 

For this reason, many companies now rely on AI for making quicker, more accurate decisions that are consistent with prior conclusions. AI also eliminates the need to double and even triple-check work for accuracy because it focuses on providing error-free feedback from large amounts of data in a matter of seconds.

In fact, 66% of decision-makers interviewed by McKinsey & Company have reported that AI has helped them increase their profits and stay on track with set goals. 

Process optimization in a product development team

AI product development processes assist with projects from beginning to end. They are focused on identifying any issues that may affect a project’s progress and offering quick solutions to eliminate potential setbacks. This includes identifying whether a team has the required skills and resources for a project or if additional team members should be added. 

Furthermore, AI helps to automate processes and provide error-free results for tasks that are otherwise prone to mistakes thus saving both time and money. 

One example of AI improving product development comes from AI’s ability to develop prototypes based on prior products. Instead of a designer being tasked with creating similar products multiple times, artificial intelligence takes over and creates designs quickly.

Better customer service 

96% of customers report that good customer service plays an important role in their loyalty to a brand. Fortunately, AI is improving product development and making positive contributions to customer service systems.  

AI helps to address customer needs and offer solutions to issues they may be facing. It can also identify and prioritize urgent needs. In addition, by analyzing the target audience’s feedback and categorizing it as negative, neutral, or positive, AI tools help companies make necessary adjustments quicker and more accurately than ever before.

Research suggests that up to 59% of purchasers can recall a personalized shopping experience that made an impact on their shopping decisions. Because AI can quickly identify a customer’s prior site history, including agent conversations and on-site interactions, companies can offer a more personalized experience each and every time a customer shops online.   

Read also: AI in business: What are the benefits of artificial intelligence?

Cost savings  

As mentioned in prior sections, AI can drastically reduce costs. By streamlining workflows and improving efficiency, AI helps optimize processes and cut down on operational expenses. It can automate routine tasks and reduce manual errors, saving time and money. Additionally, AI mitigates risk by ensuring hackers aren’t accessing confidential information. Allowing advanced security measures and continuous monitoring, it prevents costly data breaches.

AI also cuts costs and saves time by automating repetitive, mundane tasks. For instance, AI can predict when equipment needs maintenance, preventing expensive breakdowns and reducing downtime. This frees up resources so your team can focus on more strategic activities and innovation. In the end, AI helps drive better business outcomes and creates a more productive work environment.

Speeding up development processes  

Another example of how artificial intelligence improves product development is by speeding up processes throughout the entirety of projects. This is done in various ways. One is its ability to address any gaps in a project, such as a lack of skill sets or not having enough team members to complete tasks on time.

AI also assists by determining which tasks will take the longest and offering suggestions as to how certain tasks can be automated. Further, AI can support product development team members without compromising product quality — in fact, it does quite the opposite. 

Developers and testers are among those who have the potential to benefit most from AI coding assistance. By detecting any errors or issues in code, testing times are drastically reduced.  

AI in product development – conclusions

AI assists the product development process in a myriad of ways that bring countless benefits to businesses. Thankfully, these benefits are not limited to the quality and performance of products. Throughout the product development lifecycle, AI optimizes efficiency, enhances quality, and accelerates timelines. AI tools streamline the workflow, enhance accuracy, save time, and play a major role in the timeline of a product launch, competitiveness, and future business strategies.

On the topic of strategy, it’s important to clearly define your business goals and initial strategies prior to implementing an AI system. While artificial intelligence can be incredibly beneficial to businesses everywhere, it is generally not a cheap investment. In deciding what AI systems will (and will not) work for you, it’s crucial to have a clearly defined approach for the successful adoption of AI development services.