What Does the Future of AI Look Like?

Posted by Tirthankar RayChaudhuri on Sep 05,2023

Applying AI/ML technology within global mainstream technology commenced around 2016 in the wake of the data analytics industrial wave. AI was identified as a more powerful but very high computational-capacity-consuming means of gathering deep insights from business data as well as automating business operational processes. In a relatively brief timeframe the growth of AI has been truly meteoric and as per Fortune Business Insights the next 7-year growth projection of the AI market is from $515.31 billion in 2023 to $2,025.12 billion by 2030 exhibiting a Compound Annual Growth Rate (CAGR) of 21.6% during the forecast period.. The Future of AI therefore promises to be long, eventful, highly active and full of upcoming achievements.

In the past seven decades (please refer to an earlier Blog in this series for an Account of How AI was Developed) of tireless invention and innovation humans have built algorithmic reasoning that can discover patterns and learn functional behaviour from data in very high complexity spaces accompanied by algorithms that provide accurate search discoveries, predictions, recommendations and optimal parameter combinations for solving multifarious problem scenarios. The levels of industrial automation and efficiency increase derived by using such algorithms is still in its early days and over the next couple of decades, industrial AI will focus on reaping immense benefits by applying these techniques in a far more effective manner than what is occurring in the current global environment constrained by immature processes, lack of best practices and unnecessary hype and fear-mongering that is largely unfounded.

In future years vastly improved AI tools and development platforms will emerge, best practices will be in place, AI skills will become more readily available and the level of success of AI projects will improve significantly not only in delivering results within time and cost but also in the accuracy and reliability of project outcomes. Alongside of these improvements there will be in place out of necessity the regulatory safety measures we have proposed in the previous section of this Blog. In other words there is much scope in future years for industrial AI to progress towards becoming a truly mature discipline from an emerging one. As a consequence companies will run their business operations far more efficiently than they do in today’s industry landscape, benefiting immensely from the increased automation, enhanced accuracy and higher reliability of all their systems becoming powered by AI/ML.

In context of the longer future of AI however it does need to be pointed out that the capabilities of machine intelligence in place today are nowhere near the fanciful levels of ‘being able to redesign themselves and independently build more capable systems on their own.’ To quote Professor Chomsky one of the most eminent thinkers of our age, such a concern is 'nothing more than science fiction’.

Related Posts:

Dec 12,2023

Do We Need Ethical Considerations for AI?

There is much paranoia and pessimism about AI misconceptions being promulgated in an irresponsible manner by individuals who are ignorant about what A

By Tirthankar RayChaudhuri

Jul 06,2023

What is AI?

Artificial intelligence (AI) is human-like intelligence exhibited by machines or software. It is also the name of the academic field of study which s

By Tirthankar RayChaudhuri

Dec 05,2023

How Did We Come So Far? - Taking a Few Steps Back and Tracing AI's Journey

We are have now well and truly embarked upon the era of Enterprise Machine Intelligence Systems. The AI industry today is already worth half a trilli

By Tirthankar RayChaudhuri

Jan 10,2024

Structuring and Resourcing for a Killer AI Project

In general a Project Manager in Technology is tasked with planning and leading all end-to-end activities of delivering projects for implementing tech

By Tirthankar RayChaudhuri