How Startups Can Compete in AI and ML

Last year, Microsoft, Amazon, Apple, Google and Facebook acquired 13 AI-based startups. Even if your goal is to run the business yourself, there are opportunities for startups and early founders to create differentiators in the field of AI and ML.

Global players are acquiring startups not just for the product or service they offer but also to lay their hands on the top talent. 

Businesses compete not just in technology but in all industries to onboard specialists- the select few who know how to create real-world solutions from artificial intelligence and machine learning.

Whether you look at acquisition as an exit strategy or wish to build a competing product for the market, there is plenty of room for you to experiment and build using AI and ML.

Let’s see a few areas of application.

Use Cases for Startups to Tap Into AI and ML

Improve the Customer Experience

With the availability of infrastructure on the cloud, there’s a lot more flexibility for startups to build intelligent contact centers in a shrunk timespan. Remote work and the pandemic have forced companies to look at the cloud as a possible solution to everything they do.

AI and ML can help improve the customer experience with intelligent voice recognition systems and hyper-personalization of CX with data housed and processed on cloud.

With such automation, startups can free up resources and talent to work on pressing challenges and address complicated customer issues. AI and ML can be super advantageous in serving customers better or creating tailored products and services.

Enable Data-driven Decision-making

Decision-making involves handling enormous amounts of data, fishing it for patterns and basing decisions on the resulting insights. Honestly, we can’t think of a single company or industry that may not benefit from improving the quality and speed of their decision-making.

Faster and more data-driven decisions can put companies ahead of the competition, help launch new products faster, boost business intelligence, improve the bottom line and stay relevant continuously.

AI and ML seem the obvious choices when it comes to making decision-making more efficient and accelerated. 

Business Forecasting

Business forecasting has numerous use cases in all industries and organizations. Data is the new oil and organizations are always looking to leverage it to forecast incidents and financial projections.

For a manufacturing organization, this might take the form of predictive maintenance and supply chain cost optimization. For another organization, it could shape sales and marketing forecasting, revenue objectives and strategies to reach there.

As companies today generate more data every day, they need to leverage it to move forward, plan innovative products and services and transform how they do business.

AI and ML can prove essential tools in the arsenal of these organizations.

Mitigate Fraud with AI and ML

Whether it’s high-stakes industries such as fintech, banking and insurance or any organization guarding against cyberattackers, artificial intelligence and machine learning can help strengthen the security posture.

With remote workforces, companies have become easier targets for bad actors and AI and ML-based cybersecurity aims to change that.

By learning from past data and patterns, these advanced systems can detect frauds quickly. Not only that, AI can automate fraud detection and prevention so that there’s less reliance on humans and more on data, eliminating guesswork and introducing more robustness.

How Challenging is it to Differentiate your Startup in AI/ML

MarketsandMarkets predicted that the machine learning market will amount to $8.81 billion by 2022 and reshape the global economy. However, more startups talk an AI game than play it.

There are reasons. In most cases, startups don’t have access to an expansive team of data scientists and AI and ML specialists like the big guys do. But more importantly, most founders are not habitual of looking at everyday problems from an AI lens. 

However, with the democratization of AI, its accessibility and affordability will only increase from here. With some barriers out of the way, there will be more room for innovation with no-code initiatives, etc.

While it’s challenging for startups to actualize a concept with AI, given the rush and competition in the market and other hurdles, they will never cease to try to make space for themselves in this booming industry.

Work Around the Weaknesses and Leverage the Strengths

As a startup, you’re also uniquely positioned to benefit from AI and ML. Leveraging these technologies often requires trial and error to determine which products, services or functions can truly benefit from their application.

Large corporations are often not free to try out outrageously innovative ideas, but as startups, you have the power and choice to do so.

On a similar note, startups are more flexible and dynamic in switching from one mindset or function to the next. Therefore, a startup founder can set the stage for AI and ML thinking right from the get-go.

As discussed above, AI and ML applications need a certain kind of mindset to look at problems and approach them uniquely.

Moreover, startups can go deep into niche problems, unlike large corporations that often go wide. Startups can experiment, fail fast and forward. That means startups can quickly achieve in-depth knowledge about a particular quickly and attempt to solve it with an AI & ML-based approach.

By monetizing strengths and working around weaknesses, startups are poised to benefit from AI/ML. If you’re looking for AI & ML services to make the journey a bit more smooth, contact us today.

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