Head of CRM & Marketing Automation at Mountainise
Certified CRM Consultant with 10+ years of experience in Salesforce, HubSpot, and Marketing Cloud implementations.
“History repeats itself.”The Internet has revolutionized communication in a way that few other Tech Stack can rival. Remember the previous century’s primitive period of having a dial-up modem? Slowly the internet developed from kilobytes of data transfer into the capacity for live streaming and affiliates. Many analysts today compare this fast growing rate of computerization development with a sitting on a dial-up & suddenly being blasted into high-speed, that’s the point of current AI developments. Masses of companies are now wondering how they exactly could apply AI Tech Stack, but the response is not universal.
A small to medium sized business would like to make some improvements of some of its functions in the most cost-effective way. Enterprises, on other hand, might be contemplating on going for an all-out AI diverse structure across all its outlets. The aim here is to determine the right strategy for your business size and requirements.
With regard to SMBs, it is important to understand that the aim of artificial intelligence in its initial phase should be to address one or more practical issues and not to get carried away with expensive robust AI systems. As was said before, there is no need to go paranoid about AI solutions which are not cost-effective in the current business environment.
With these applications, SMBs can start off with a modest amount, gauge the successes, and expand as they deem fit. It’s analogous to AI being your computer convincing your ever-busy mind to delegate the unnecessary work so you can think of ways to do better.
In terms of needs and resources, enterprises still differ. On this level, AI would target optimization on an enterprise wide scale which covers a range of utilities from predictive maintenance in the manufacturing sector to providing a respected customer experience in the retail sector.
However these tools are robust in what they offer, they are not easy to use. Enterprises can have such sophistication in tools, but they also have the challenge of intensive integration and deployment.
With regards to creating the AI Tech stack, the following simple structure can be used both in SMBs and enterprises though at different levels.
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As sometimes said by leading influencers in AI, such as Andrew Ng, a strong foundation in data is so critical. His advice? “Without good data, even the best AI models will struggle.”
Remember, when considering AI, it doesn’t mean replacing life with robots but enhancing the work that they do. A very good example would be in the insurance industry: taking humans who are going to use their precious time for days doing some repetitive data entry, enabling them to hire Python and AI tools pulling data, which in turn will make the data usable. This approach allows humans to focus on analysis and decision-making rather than collecting data.
According to Gartner, by 2025, 80% of businesses will have some form of AI in their operations. For SMBs, this means experimenting with tools that save time and improve efficiency. For enterprises, it means creating systems that scale to support a complex network of data and processes.
Every business is unique, and its journey to AI will be singularly different. Be it a lean startup or a global giant; an organization will find an AI solution fitting its needs. Find the tool that best serves your goals, and start your AI journey today.
Schedule your free working session with Mountainise today! Together, let’s unlock the true potential of your business with the right AI tech stack and drive your growth forward!
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