How many of you have read the book Frankenstein by Mary Shelley or watched the 1920 fictional play R.U.R. (Rossum’s Universal Robots) by Karel Capek?

If you haven’t and you have an inclination towards Artificial Intelligence, you must. That’s where I see the roots of artificial intelligence, stepping out through creative brains.

Perhaps, many industry experts call AI a blend of technology and creativity.

It was during the mid-1950s when AI research started to explore the possibilities. What started as an academic discipline at a workshop at Dartmouth College in 1956, is today a full-fledged industry empowering numerous industries.

It is expected that the global AI market will reach $60 billion by 2025. Backing this analysis is the exorbitant funding raised by AI startups.

According to a report by CB Insights, the investment figure reached $17.9 billion in the third quarter of 2021. Industry experts are affirmatively looking at a commendable hike in this figure.

Other reports revealed that investment in AI startups grew 6 times in the last 2 decades and the number of startups grew by 14 times.

Numerous businesses, especially startups, are coming forward with an innovative and problem-solving approach.

One such example can be noted with recent funding led by Gradient Ventures of $6.3 million for Mage.

According to Tech Crunch, the startup is developing an AI tool for product developers that can be built and integrated.

As quoted by founder Tommy Dang, “We worked with hundreds of developers having internal systems and great ML tools to launch models.

But most of them didn’t know how to use those tools. That’s when we decided to build tools for technical non-experts.”

Challenges Faced by Businesses in AI Startups


While most of the industries noticed scattered growth moving without a direction, the AI startups like Mage are impeccably adding value to the expected future.

However, it’s undeniable that there is a certain set of challenges that businesses are facing to implement AI. Some of the key challenges include:

Lack of Understanding the Need

Adopting artificial intelligence over traditional ways is a huge shift. This is further followed by the challenge to convince stakeholders about an unclear result.

It’s surprising that with so many technological advancements and the benefits that follow, still companies fear overhauling their Modus Operandi.

The reason here is understanding the need for AI. Most companies that haven’t yet integrated the technology, are unaware of the purpose they can solve.

While the technology has been around for decades, there’s a need to create awareness and educate non-technical sections about the perks of artificial intelligence.

Lack of Appropriate Data

To build and implement AI requires a good amount of high-quality data.

Companies at times fail to make proper investments in data management systems. These systems play a pivotal role in enabling AI. The failure will eventually leave you behind with no algorithm to solve business problems.

Having a CRM tool that can help you collect data like customer behavior, demographics, on-site interaction, purchase pattern, etc. Eventually, the gaps can be filled using online data libraries and synthetic data.

But if you don’t have a general interest in AI, you might not be able to realize the data you need, making it a forgotten fable.

Lack of Skillset

Ascertaining the data is just the first step. Skills to utilize data are a must-have to get AI at work.

Most companies fail to hire machine learning and data experts, which eventually restrain your ambitions to move further. Additionally, some companies manage to onboard the resources but lack experience. This eventually slows down the progress.

Having said this, the impact can also be noticed in the hiring process. That’s because the hiring managers often aren’t aware of assessing the right candidates and roles to be filled.

It’s also been noticed that the HoDs (Head of Departments) are sometimes underqualified to lead the process. This results in integration issues, ongoing manual work, or inefficient processes. Eventually undermining the value of solutions.

Inability to Find an Appropriate Use Case

Without proper company-wide adoption, the strategy may have a negative impact.

Without a flawless use case, the company will struggle to make a certain solution that provides business value. As a result, there won’t be concrete proof of how artificial intelligence can solve challenges.

If you don’t have a clear idea of how you’ll use AI, it’s better to delay it until you find the answer.

The Team Fails to Explain How a Solution Works

To trust a computer as a model, it’s important for an individual to first understand it.

Acknowledging this, if the AI team can’t explain, the implementation would end then and there. Challenge primarily comes when there’s a conflict in stakeholders’ expectations and model output.

To better understand this, let’s take an example. If a doctor is relying on a machine to diagnose the patient and the algorithm disagrees with it, he/she should understand the reason behind it.

If the model considers sneezing and headache to determine flu and doesn’t consider the age or weight of the patient, this will eventually lead to poor/wrong results that won’t help you identify the exact disease and diagnosis required.

AI is Ready for Businesses. Are Businesses Ready?


AI has evolved and transformed itself into a long-term solution for not just the challenges above, but more than that. While AI is prepared for businesses across various verticals, the question is are businesses ready?

While a flawlessly powered AI model can enhance productivity by 40%, it’s important to determine how. Here are some key ways you can prepare yourself to leverage the best out of AI implementation.

Moving Early

Artificial Intelligence has immense scope for transformation with the right data in the hands of skilled people. If you’re aware of the tool and ways to use it, you shouldn’t delay it further.

The significant loss that can be mentioned here is in context to your growth rate. You can undoubtedly reach new benchmarks by implementing AI in your business.

Striking a Balance

You need to strike a balance between quick tactical wins and your long-term vision. Both should go parallel to attain unprecedented results. You need to identify and automate quick wins that have the highest automation potential and have a close eye on comprehensive transformation over the long run.

Long-term Vision

While AI is known to give quick results if implemented and used properly, experts have always emphasized having a long-term vision. You got to know how your future transformation can be automated and further be utilized to achieve maximum growth rate. Don’t forget pounds to come in the future while collecting pennies today.

Redefine Processes

McKinsey’s report shared that 60% of jobs have the possibility of at least 30% automation. This includes redefining jobs and taking an end-to-end process view.

Each of them is necessary to attain value. Moving forward, you’ll have to redefine your work process. You’ll also have to manage organizational changes that will follow the AI implementation. Successful execution will eventually reap productive growth.

Getting to the Core

Build and integrate AI into the core model to attain lasting value and have a transformative impact. Fall in love with not just collecting data but also learning how to make informed decisions.

Simultaneously, you should have a continuous hunger for improvement. This is because AI is an ever-evolving technology, and the best can be leveraged when you are open to future improvement patterns.

AI isn’t the future!! You need it today.


Ever wonder what would happen if one of the asteroids from a fictional movie published on Netflix, actually landed on Earth? Unimaginable but disastrous for sure. A few years back nobody knew that AI would play a vital role in identifying such threats.

I came across a write-up on this that introduced and explained project CIMON by Airbus and IMB to me. Over the years, numerous industries have adopted and implemented AI into their core modus operandi.

Acknowledging this, space exploration isn’t the only industry making profound decisions using AI. There are numerous other businesses across vivid industries doing the same.


AI and ML have introduced new verticals of data processing to the retail industry. According to CB Insights, funding in retail AI has touched an all-time high of more than $100 million. This includes handling first-party data analytics, and concerns like eCommerce fraud, fulfillment, etc.

From customized promotions to inventory management, AI is redefining the entire retail landscape. Companies have harnessed AI to attain innovative solutions.

Some noteworthy examples to consider include PepsiCo’s micro fulfillment centers in partnership with Dematic, Kroger’s vision-powered smart shopping carts, and much more.

Electric Utility

Recently, the electric utility industry is going through a storm of challenges like energy diversification, growing competition, and less regulated & complex markets.

AI is a technology that has proven its capabilities through complex algorithms that entail it. The electric utility industry isn’t untouched by the wonders of technology.

It plays a crucial role in fault prediction, managing renewable resources, maintenance through image processing, disaster recovery, and much more.

Like other industries, AI is also assisting the electric utility industry by enhancing energy efficiency through prompt decision-making. Utilities like Innowatts and Autogrid have proved how AI can be of great help if integrated smartly and with precision.


Challenges like machine failure, quality assessment, maintenance, inventory management, etc. are common and impact largely on the growth and sustainability of a manufacturing unit. A report published by McKinsey, for manufacturing units, AI can enhance forecasting accuracy by 10-20%.

Having said this, you can eventually increase revenue by 2-3% and reduce inventory cost by 5%. The need is to look at the prevailing functions where traditional analytics can be leveraged.


The Healthcare industry has noticed a significant improvement in computation power resulting from speedy data collection and processing. A widespread implementation has been noticed in managing and maintaining health record systems.

AI has also proved its worth by improving precision in robot-assisted surgery. Over time, AI in healthcare has commendably helped in the early detection of diseases.

According to a report, AI has helped healthcare professionals to detect mammograms with 99% accuracy. And this was attained 30 times faster than traditional ways while surpassing the need for biopsies.


In a report published by market research engine, it’s expected that the use of AI in the education sector will reach $5.80 billion by 2025, featuring an exponential growth rate of 45%.

AI is playing some of the leading roles in the education sector including task automation, personalized learning, universal access, smart content creation, teaching the teacher, identifying classroom weakness, 24/7 assistance, etc.

The implication is primarily bifurcated in three segments by model, namely, Learner model, Domain model, and Pedagogical model. Needless to mention, looking at the evolution, the models aren’t confined to the mentioned list.

Concluding Note

AI has been playing a pivotal role in transforming the way businesses work. The implementation isn’t confined to an industry or two. It has spread itself and is largely adopted by SMBs and brands across various industries.

While technology is evolving rapidly, it’s crucial to have a team of skilled technocrats that can lead you through the right path. Once attained, you can make the most out of AI in your business.

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