Artificial Intelligence and Manufacturing Limitations

By Author: MENTit (MENTit Developer)
Affiliation: MENTit Mentor

In a recent survey by New Vantage Partners as reported by IBM, 81% of Business houses across the globe have no idea of the requirement of Data in the age of Artificial Intelligence. Out of total Fortune 1000 Executives surveyed, 73% have said they got measurable results, while, 24% acknowledged transformative & innovative results.

AI draws upon knowledge and techniques from mathematics, statistics, computer science and domain-specific expertise to create models, software programs and tools. These software programs and tools can undertake complex tasks with outcomes that are comparable, if not better, to traditional manual approaches.

The limitations:

 But is manufacturing industries limited to IT skills? AI alone cannot run any industry. AI is not efficient by itself; AI is a tool to efficiency. Technology is not the disruption, not having right skill is.

Is Data Scientist the answer? Modelling scientists with IT Skill, mathematics & statistical knowledge have to be supported by Decision Scientists with respective domain expertise across functions. No one leader can wear the entire hat to build AI infrastructure to claim he has complete knowledge or business acumen across all domain.

Few References:

  • In a recent finding of World Economic Forum across EU, China and US surveyed reveals:
  1. Seven out of ten manufacturers fail to push initiatives in big data analytics, AI & additive manufacturing.
  2. Successful beacons should serve as a good model for how to successfully implement IIoT solutions that provide tangible financial and operational impact
  • Enno de Boer, Partner and Global Head of manufacturing at Mckinsey & Co on three successful companies surveyed “ These pioneers have created factories that have 20-50% higher performance and create a competitive edge. They have agile teams with domain, analytics, IoT, and software development expertise that are rapidly innovating on the shop floor. They have deployed a common data /IoT platform and have up to 15 use cases in action. They are thinking scale, acting agile and resetting the benchmark.


Growth is directly proportionate to shrinking leadership ability. Disruptions and growing business complexities are the biggest organisational dilemma. No leader can wear all the hat to claim he has full knowledge of business process across the entire organisational domain to define the data requirement and integrate into the system for necessary analysis and best results.

Digital investments should not be restricted to back end office work, or, as support assistant only. Its direct use in value creation to create a competitive edge through an increased return to scale for direct and quantifiable benefit is the key and pre-requisite.

 A basic level of human capital, such as literacy and numeracy, is needed for economic survival while addressing following fundamental challenges for being competitive enduring growth and stay relevant under new normal. The growing role of technology in life and business means that all types of jobs (including low-skill ones) require more advanced cognitive skills (The Changing Future of Work by World Bank Group).

  • Arranging real-time matrix to monitor, control & ensure a dignified return in the cost of capital employed
  • Leveraging Operation, they have to arrange econometrics for real-time monitoring of operational cost weighing decisions against real-time cost while neutralizing macroeconomic implications at the micro level of operation. Productivity analysis and analysing each activity of the business using tools of AI is mandatory and obligatory on the part of Business Leaders for being competitive and stay relevant under new normal and VUCA world.
  • Striking a balance between elements of prosperity and factors of production is mandatory to optimize operational cost.
  • Digitization with real-time data accessibility, both structured and unstructured data.
  • Ensure high-quality reliable data.
  • A clear vision of various reports required to analyse the operation on a real-time basis, for cost and financial analysis, customer analytics etc
  • The requirement of relevant talent. This may add up to cost several times.

Successful organisations will be able to reduce/optimize their operational cost through productivity analysis and efficiency. Technology is blurring the boundaries of the firm, as evident in the rise of platform marketplaces. Using digital technologies, entrepreneurs are creating global platform-based businesses that differ from the traditional production process in which inputs are provided at one end and output delivered at the other. Technology is also reshaping the skills needed for work. The demand for less advanced skills that can be replaced by technology is declining. At the same time, the demand for advanced cognitive skills, socio-behavioural skills, and skill combinations associated with greater adaptability is rising. Already evident in developed countries, this pattern is starting to emerge in some developing countries as well.

Upskilling white collars & non-IT professionals with Business Skill of Fourth Industrial Revolution-Through Engineering across the value chain and of the respective domain for productivity analysis in line with requirements as enumerated above is the only available option to succeed and contain cost.

The reason behind, such skills, though not available, are being valued in the market between US$1,23,000 - 2,28,000. Such employment cost is sure to create the bankruptcy situation.

With four decades of leadership across diverse industries, we are second-to-none in developing such business skill. We offer two-days highly specialized unique and exclusive educative discourse on Economic Engineering and Econometrics suitable for Policymakers, Decision makers & Executors. Our expertise has been retained by various international institutes/organisation/forum. We may be contacted for necessary help.


World Economic Forum, Mckinsey, Industry Week, IBM,World Bank Group

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