Product Design and Development – Going the AI Way
Published on : Monday 30-11--0001
As the digital revolution impacts the very way any business is carried out, one of the most prominent trends to look out for is Artificial Intelligence (AI). There is no denying that AI is breaking down the obstinate business barriers at an astounding rate. Be it the dynamic manufacturing or the cautious healthcare or the evolving automotive or the ever pervasive agriculture industries, AI is already present in almost all the major industry verticals and growing stronger every single day.
If we go by recent studies, for example, the latest report by Markets and Markets predicts that AI will be at an overwhelming USD 190 billion by the year 2025 owing to the rise in cloud-based solutions and applications, upheaval in big data as well as in growth in the demand for virtual assistants that are intelligent and predictive.
AI can help solve issues in the field of creativity, problem-solving, critical thinking, analytical thinking as well as systems analysis. When it comes to new product development, AI is not something you can ignore. With AI in place, new relationships are established between the consumer and the product. The interaction between the business and the customer is leading to further innovation in the field of new product development.
The role of AI in product development
Not sounding too futuristic, AI is likely to outrun human resources in terms of intellectual task processing by the year 2050 (according to a recent AI Conference). One of the many aspects of AI intervening with human life and experiences can be seen in recent demand in producing better than higher quality goods. To sum up, the competitive global market is continuously pushing enterprises to upgrade their manufacturing lifecycle with better products with superior design and enhanced performance standards. It’s not just a need but a mandate today to correspond to this need. Product managers are expected to scale up their technology kitty with AI powered specifications as well as data science and data engineering features.
Top 3 areas transformed by AI – Process, Product and Analysis
As a matter of fact, AI has already been crucial to various aspects of the design and development phases for any major product. For product development, AI-based apps and software act as an interface between machine and human beings, and this works well in both General AI (GAI) and Applied AI (AAI) functionalities. GAI boasts of machine intelligence that allows intellectual tasks to be performed by a machine, while AAI is about in-depth machine learning and predictive analysis, to both learn as well as adapt. The top three aspects that are affected:
- – Mostly AI-based products are interactive apps and complex software services which employ AAI and machine learning to keep their users informed and well assisted. Service-bases systems and processes, when aided by AAI offer highly consistent production without major interruptions. This, in turn, improves efficiency, reduces cost and time to market and eliminates repetitive tasks to free up human time and energy.
- – AAI has made some tremendous impact on product development by offering tangibly superior new products and processes that suit market needs with the best possible technical and commercial options. From traditional processes to dynamic parallel processes, AAI has significantly reduced product development and manufacturing cycle time.
Analysis – Sequential analysis of computational data is highly crucial to analyse risk factors involved in product development keeping on with market and user details, requirements and conceptualisation. AAI further aids in simplifying complex tasks and offers the much needed strategic outlook to product design and development.
Some of the astounding cases where AI made a huge impact
Today, if we look around, some of the big noise has been created around Airbnb, a hospitality hub spot with a huge following that utilised production-ready design components to move away from hand-drawn wireframes by incorporating machine learning as well computer-vision-enabled AI. Similarly entertainment application mogul Netflix uses augmented intelligence to personalise and localise art and show banners to global languages for increased audience interaction.
A favourite sweetened sandwich spread brand uses an AI algorithm to generate unique packaging options for the brand. Keeping the graphic identity intact, these packaging options are unique in look and appeal.
Talking of a more progressive future, AI is now used to train robots, and technology leaders like Siemens have now adopted AI to decipher complex CAD codes to assemble robot parts.
Future of AI in product development
When it comes to design, AI helps designers, developers and product managers to create designs that will be more easily acceptable to users and also offers more options in terms of product improvement. The whole need for personalisation and localisation of products to make users comfortable can be answered with AAI. When it comes to manufacturing, products that are designed following specific patterns laced with AI, are more likely to reduce manufacturing trial and error cost and also offer the key to future factories. Be it pattern and voice recognition or machine learning technologies, AAI aids in quicker resolution to AR, VR and MR products, which all demand a great deal of design work. When it comes to Aftermarket, bringing in a model that is self-sustainable, laced with AI and machine learning, will allow engineers to predict any problems and prevent it, throughout the entire lifecycle of the product.
AI is ready to aid not just product development and manufacturing but works towards stringent quality control to reduce cycle time and materials waste while improving production reuse. The other aspect being predictive maintenance, which can be aided by deep-learning to solve a multitude of problems in varied domains.
With the option to churn a huge amount of data with powerful computational software and hardware armed with diverse and focused algorithms, product managers now can think about rocking the markets with newer and more progressive products.
Challenges in achieving success with AI
A successful AI-led product requires three skill pillars covering all aspects of product development, namely feasibility, desirability and viability. A true AI-first strategy needs the top most talent in terms of machine learning, designing, engineering, product development as well as strategy.
As a first step toward the AI-first journey, the organisations need to embrace the precise vision, culture and incentive mechanisms to attract, retain and develop talent with AI expertise.
Utilising the true power of AI
There is no denying that AI is all pervasive to optimisation and speed when it comes to product design and development right from the conceptualisation to detail design to production and delivery phases. OEMs today need to look at how to utilise AI for their vital product developments to speed up the design prototyping process by incorporating machine learning and how to align the product to match the actual branding requirements.
Looking at the creation of products with help from computer vision, speech recognition as well as natural language processing, OEMs get help from engineering services companies that have expertise in both machine learning and deep learning to create models that can learn from data be it in the form of image, text or audio.
The future looks pretty promising with the introduction of AI in product development and there is no turning back!
Captions
Pix1: Product managers are expected to scale up their technology kitty with AI powered specifications.
Pix2: Products designed following specific patterns laced with AI, are more likely to reduce manufacturing trial and error cost.