How AI Is Improving New Product Development

Apr 27 2022

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Demand for AI In Product Development is Rising

Artificial Intelligence and its subset Machine Learning are constantly pushing the boundaries to establish roots across industries, from automotive to pharmaceuticals, retail to education, manufacturing to energy, and utility. According to MarketsandMarkets, it has been that the AI development market is expected to grow from $86.9 billion in 2022 to $407 billion by 2027.

With the speed of technological changes happening faster than ever, companies must innovate to thrive in this cut-throat competition where a new product is launched every day. Prototyping, designing, and developing must be efficient to stay competitive and cost-effective. 

To get new products launched with the speed of a market opportunity, AI and machine learning are opening the way to accelerate and improve new product development processes.

Impact of AI on Product Development

New product development is devising a market-ready product that answers an opportunity or a real-world challenge. In the current times, AI development can accomplish a lot of actions accurately. One of the significant advantages of AI superseding human experiences can be seen in launching higher-quality products. Turning to AI software development can simulate and accelerate the development process and upgrade the manufacturing lifecycle with better products, superior design, and enhanced performance standards.

AI can be grouped into General AI (GAI) and Applied AI (AAI). While General AI includes Machine Intelligence, Applied AI covers machine learning and predictive analysis. AI is tapping into every aspect of product development. Therefore, putting AI into architecture is not merely a need but, in fact, a mandate.

Time is a Crucial factor in New Product Development

Generally, it takes several years for an idea to go from conception to a commercially valuable product. In the early phases of the development, potential product opportunities are created. Then, commitments are made for resource allocation. And there are chances that resources for those possible products may lead to potential future failures. The inability to foresight during this product development phase is painful regarding the time spent. Time is a crucial factor when it comes to the development of a new product. As it accounts for a large portion of a company's profits and holds a strong competitive advantage, rolling out new products quickly is of utmost importance to a company.

Artificial intelligence can be used to accomplish digital testing and predictions of prototypes before a company allocates time and teams to running the physical product trials.

Top 5 Factors How AI Uplifts Product Development

With a tsunami-like power, AI and ML continue transforming how we engage and navigate the world. Advances in AI-based apps force the convergence of other revolutionary technology like IoT to support and improve new product development processes. Let's take a closer look at how AI helps in uplifting new product development.

Driving Efficiency Using Product Lifecycle Management

The fast launch of new products needs an integrated partner ecosystem that incorporates a culture of co-creation where multiple stakeholders and partners work together. AI algorithms produce accurate results when they are fed with high-quality data.

PwC's research found that digital product development is expected to uplift efficiency by 20%, reduce product launch time by 17%, and production costs by 13%.

Strategic partnerships augment data quality, which further impacts prediction accuracy. For example, Amazon teamed up with a few clinics in the USA to train Alexa to understand different kinds of human sounds like coughing, hawking, sneezing, etc. Thus, digital product development teams that work on AL & ML achieve greater efficiency and speed gains in the product designing and development stages.

Improving Demand Forecasting Accuracy

Eliminating the roadblocks to releasing new products faster starts with implementing AI technology to improve demand forecast accuracy. For example, Honeywell uses AI to reduce energy costs by tracking and analyzing product price elasticity. The company is leveraging AI and machine-learning algorithms in various operations, including procurement, cost management, and strategic sourcing, to receive stable returns across the new product development process. Businesses are keeping the race on to predict the future to reverse engineer to adjust or re-imagine supporting functions.

Another excellent example is XpresSpa, the world's largest airport spa chain, which implemented AI analytics to eliminate the uncertainty of footfalls in forecasting sales on any given day. The algorithm analyzes the relevant data points that directly and indirectly affect the throughput of spa customers and predicts the sales of a location in their new application.

Fueling up Cross-sell and Up-sell Opportunities

It has become common amongst businesses to work on data-driven new product development using propensity models (used to predict the likelihood of specific actions performed towards purchasing a product). Such propensity models are based on imported data from Microsoft Excel, which is time-consuming. Putting AI into the setup can streamline the creation of the propensity model and can fuel revenue contributions derived from up-sell and cross-sell strategies.

Reducing Time-to-market and Improving Product Quality

Now it is possible to synchronize better suppliers, technical teams, DevOps, product management, marketing, and sales to achieve success for a new product in the marketplace. BMC's Autonomous Digital Enterprise (ADE) is one of the excellent examples that delivers next-gen business models for forward-thinking organizations interested in reinventing their businesses with AI/ML capabilities. This ADE framework is more flexible enough to respond to customer requirements than other competitive frameworks. BMC's ADE framework is the future of digitally driven business frameworks that can support scalability for new product development.

Optimizing Processes for the Product Development Team

AI, when implemented correctly, can assist the product development team from the beginning of the product idea to the actual product launch. Artificial intelligence focuses on optimizing the product formation process by diagnosing hurdles that may harm progress. Moreover, AI-integrated processes sometimes cannot just analyze but also eliminate any risk factors beforehand that could have developed limitations in ensuring a smooth development implementation process.

AI hyper-automates processes and generates error-free insights that may have been prone to mistakes. Thus, this technology assists in optimizing a process, as well as saving time and investments.

To dive deeper into how AI optimizes the processes for product development teams, consider a situation where a person is assigned the task of manually developing, forming, and testing product prototypes. It can be very time-consuming as well as costly through manual power. Now consider if the same task is integrated with AI algorithms will save time by multi-tasking and developing product prototypes and testing and suggesting the most suitable product outcomes if the AI model is trained correctly with data extracted from prior successful prototypes.

Providing Recommendations on Improving Product Usability

Generally, DevOps, engineering, and product management teams generally run A/B tests and multivariate tests to find usability features, workflows, apps & services that customers enjoy. One of the most challenging aspects is designing an intuitive user experience that turns out to be a strong product with practical usability. AI algorithms like generative design will help identify design constraints and provide insights around product usability to make the experience more engaging.

Take Your Next Step with AI to Improve Product Development

AI offers agile companies the competitive advantage for new product development to gain a strong foothold in the market. AI is reshaping the product development cycle with so many benefits including lowering the cost of doing business, allowing automated testing of features, and assisting with user experience and design. Companies turning to AI/ML capabilities are not just focusing on algorithms, programming, and data engineering. They are paying attention to underlying data models that make the entire development process possible and efficient.

As one of the leading artificial intelligence companies, Icreon helps businesses get to market faster and improve their competitive position while reducing manual labor & guesswork in their next product development journey. Explore Icreon's Digital Product Development Services.