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 (AI) to this success factor list. There are many reasons for its adaptation – quicker decision-making, process optimization, improving customer service, cost reduction, and overall, ramping up their product development processes, among others.
In this article, we will explain the benefits along with 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 system(s) for your business.
Integration of AI in the product development process – how can it help?
Integrating an AI product development process can support many aspects of a business. From architecture to manufacturing, AI has something for every industry. Below, there are seven areas that are being improved by AI integrations today:
AI-powered 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 taking out 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, the algorithms leveraged by AI 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 experience 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.
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 makes 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 toward said requirements.
It’s important to note that AI tools should not be viewed as a replacement for specialists. Rather, they function as a wingman that helps guide them through their processes more efficiently.
Artificial intelligence 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.”
Benefits of AI in product development
There are plenty of examples of AI improving product development. Below, we will focus on five core areas, which include quicker decision-making, process optimization, better customer service, cost savings, and speed up development processes.
Quicker decision making
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 the progress of a project and offer quick solutions to eliminate any potential setbacks. This includes identifying if 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 even goes one step further to prioritize urgent needs. In addition, by providing feedback that is categorized as negative, neutral, and positive, companies are enabled to make any necessary adjustments quicker 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.
As mentioned in prior sections, AI can drastically reduce costs. From process optimization to mitigating risk by ensuring hackers are not accessing confidential information (or any information at all), AI improves product development through cost reduction.
AI also offers cost savings and improves time management through automation and assistance with repetitive, mundane tasks.
Speeding up development processes
Another example of artificial intelligence improving product development is by speeding up processes throughout the entirety of projects. This is done in a variety of 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 act as support for product development team members without putting product quality at risk. 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. AI also plays 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 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.
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