How AI can be Beneficial to Grow Business of Small Enterprises
Nowadays, Artificial Intelligence (AI) is Buzzword for the IT Sector. Giants of IT such as Amazon and Google are started to take leverage of this technology, as people response is good with this technology. A small firm can also use AI and take benefits of this technology, such as in Mobile App Development.
AI and ML apps are almost everywhere, from stared with ride-hailing services to Voice search on smartphones, we use AI services every single day-It feels so accessible to us. Can AI be reached within a small business?
Fortunately, for businesses on a budget, one does not need to break the bank to start incorporating Artificial intelligence and Machine Learning into their operation. By launching on a smaller scale and leveraging ready-made solutions, one can effectively harness the capabilities of AI and improve performance across different departments considerably.
Here are three best approaches that can use in AI in SMEs right away,
1. Take advantage of existing platforms
If you develop your own AI is undoubtedly a complex and time-consuming process and requires a considerable amount of investment. But thanks to those tech companies, which launched their own open-source AI platforms. This is a genuine effort by that AI can reach to more and more consumers. To take advantage of this platform for your business saves you considerable cost and time, required in developing and designing.
Let’s take a look at some popular AI platform which can be useful for your business,
i. TensorFlow
TensorFlow (TF) is released by Google in 2015. It is one of the most popular widely used frameworks for Machine Learning. TF is used to develop research and production objectives, TF is now widely used by numerous companies, including Dropbox, eBay, Uber, Twitter, and Intel.
ii. Spark MLlib
Spark MLlib is developed by Apache, it is a machine-learning library that supports Python, Java, Scala, and even R. Spark MLlib is specially designed for processing a big amount of data and could quickly be deployed across various Small or Medium-sized Companies such as, finance, healthcare, manufacturing, and many more.
iii. Keras
Keras is known for its modularity, and ease of extensibility. The feature that makes Keras unique is that it could be applied as a bolt-on and stand-alone software as well. Keras designed to simplify the creation of deep learning models.
This platform is written in python, it can be deployed on top of other AI technologies such as TensorFlow and CNTK.
iv. Caffe
Caffe is an abbreviation of Convolutional Architecture for Fast Feature Embedding. Caffe is introduced in 2017. It is a Machine Learning framework that primarily focuses on expressiveness, speed, and modularity. This open source platform is written in C++, and also comes integrated with a Python Interface.
Features
i Extensive Code
i Quick Performance
i Expressive Architecture
i Active and Vibrant Community
Caffe is an ideal platform for its active community provides on-the-go solutions and it is easy to deploy.
2. Implement AI for Analysis
If you trying to implement AI for your business and you don’t want to invest heavily in machine learning then analytics is a better option.
AI-powered analytics software will help to earn with business intelligence applications. Here is a list of some of the best analytics software,
i Amazon Machine Learning (AML)
AML is a Machine Learning service that offers tools and wizards to create Machine Learning Models. With the help of easy to use analytics, Amazon set the aim to make Machine Learning more accessible than ever.
i H2O
Microsoft has developed an open-source software framework that competes with platforms like Caffe and TensorFlow. The solution enables enterprises to rank efficiently across multiple machines on large datasets.
3. Start with Small business
AI enablement can’t be achieved overnight. Trying and rushing into the process is definitely a detrimental approach. Going all-in and investing massively is not recommend for small and medium scale business. SMEs need to keep patience and start slow then increase their AI efforts gradually over time.
Below is a structured approach as to how to proceed,
i Start by integrating first-party apps that facilitates productivity of the already employed workforce.
i Once ready, steer your efforts towards open-sourced AI, cloud systems and flexible workflow models.
i Start with a small problem with a high chance of demonstrating a positive return on investment (ROI). For that follow these three steps.
Define: Define clear expectations of what AI can and cannot do for your specific business profile.
Measure: Measuring should be done against meaningful baselines.
Decide: Decide whether the experiment worked or not.
Benefits of AI in Small Businesses
AI can drive considerable breakthroughs for SMEs across many departments. Though AI is still evolving, we are starting to believe that it will change the way businesses are managed through the level of offered technology. Many organizations have begun implementing AI into their business workflow and are seeing a notable improvement in ROI and business turnover.
Below are some points which can help small business owners to adopt AI,
1. Highly efficient customer service
Customer nurturing is acquired for any process. Support is crucial to retain a customer, and sometimes support agents fail to deliver unique and relevant solutions to their customers. Through AI enabled support services, this anomaly could be readily solved.
2. Important insights into the competitor’s business process
Studying the competition thoroughly is important for understanding market trends and staying competitive. AI-based analytics software provides much more significant and relevant insights into the business process of your competitors.
For instance, AI-powered competitive analysis tool, Crayon helps to track your competitor’s activities across different channels like websites, social media, and web applications. This functionality enables small business to get a better understanding of ongoing changes in the competitor’s strategy.
3. Off the rack solutions
Small enterprises can deploy off the shelf tools into literally all element of their business workflow involving data. These solutions give not only better insights into the process, but also suggest better solutions for the problem. For example, AI enabled tools, such as Monkey Learn uses technologies like entity extraction and sentiment analysis to derive a better understanding of the business. Moreover, it doesn’t require the user to code and is extremely easy to integrate.
4. Transform your Marketing process
AI is fundamentally changing marketing from the roots. AI-based advertising platforms have already been deployed by huge enterprises like Facebook and Google to target specific customer-set who are receptive to their message. This is just as true for small businesses to start leveraging and integrating AI now if they want to reach potential consumers in the future.
5. Cost and Time benefits
It is fruitful for SMEs to utilize deep learning because it can end up saving a lot of money spent on employing extra employees or outsourcing for specified projects. When repetitive or time-consuming work is done fast and efficiently at the push of a button then employees are freed up to do creative work that will help the company grow.