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Tag: Artificial Intelligence online training

AI Pitfalls: The Reality of Implementing AI

Posted on by Imarticus Learning

There is no denying the rapid rise of AI. Since 2012, AI has become an almost essential part of every sector of business. 

In medical sectors, AI is making breakthroughs, be it precision surgery, making it safer to go under the knife or in banking, the AI interface has made transactions and customer care-a breeze to walk through, AI is even making its way into the F&B industry with automated smart stoves and microwaves.

Consider most tools you use on a day to day basis have AI, your smartphone now can be unlocked by facial recognition and biometric scanning, both are developments in AI. Your home security system has the same features. You can now enable smart home features using AI products like Alexa from Amazon.

The potential for AI in businesses too is immense, consider that your company can have an automated assistant to perform any task a person would have had to do in the past, this includes making appointments, sending out reminders for important dates and filing.

Artificial Intelligence can also be used for employee recruitment, simply enter specifics into your AI database and let the candidates be chosen for you in minutes. The same can be said of the research, no matter what business you run, you will need research and development models, AI voice search engines like Siri and Alexa in the workplace can streamline research time by providing ready solutions to specific problems.

There is a catch, however, while the potential and benefits of AI are immense, it is important for small businesses to understand that this tech is still in its infancy. Therefore, pitfalls will follow. One of the most common pitfalls for companies looking to integrate or implement AI in their offices is that they are caught up in the hype of the potential of AI rather than what it can currently do for you now.

Another major pitfall to consider when looking at AI for companies is AI management requires an adequate IT team who are knowledgeable in the field, since the field itself is in its infancy, finding adequate management help can be tricky.

One major pitfall to keep in mind is that while AI can reduce costs for operations of a business, it is essential that you don’t depend on AI for all your organization’s solutions, AI has not reached a level of customization where it can solve your company’s unique problems with general solutions. One more major pitfall of using AI in the office is that it can create insecurities amongst the employees, AI still carries an air of mystery which can cause insecurities to the human element in the office, thus creating an unstable working environment.

In conclusion, it is important to remember that AI has immense growth potential and has the ability to streamline your business for the better. It also is still growing including the skill required to manage it. The limitations of AI for your organization specifically and the impact of AI on your employees are all pitfalls you must consider before implementing AI on your company or office specifically.

So before you integrate that AI system to your business, understand what AI can and cannot do for you and your company rather than what it may be able to do in the future due to its potential.
References
https://dzone.com/articles/4-artificial-intelligence-pitfalls
https://www.artificial-intelligence.blog/news/pitfalls-of-artificial-intelligence
https://www.forbes.com/sites/forbeschicagocouncil/2018/06/15/five-ways-ai-can-help-small-businesses/#4d2cead310d7

Using Artificial Intelligence in Indian Farming Sector: The Way Forward

Posted on by Imarticus Learning

India’s roots and foundation have been agrarian, and they continue to remain so. The India Brand Equity Foundation (IBEF) reported that 58% of rural households in the country depended on agriculture for their livelihood, as of 2018. On the level of the national economy, agricultural services and machinery industries have led to a cash influx through foreign direct investments of about $2.45 billion. 

Looking at these metrics, it is clear that the agricultural sector has much to gain through the use of technology to advance its crop yield, in ways that grow the sector and benefit the farmers. The field of. Artificial Intelligence (AI) has shown scope for widespread application and impact. The most popular uses of AI in farming span the life-cycle of sowing, caring, harvest, and selling. Here, we detail some applications of AI usage in the farming sector across different periods of harvest. 

Predictive Technology
Predictive technology such as Microsoft India’s AI-based sowing app has addressed a critical issue of the right time in crop sowing. The right sowing time cuts losses through seed costs and fertilizer applications. To automate this through historic data, this predictive app uses data from over 3 decades to determine the optimal sowing period, which is then shared with the farmers via text messages. The findings from their pilot run indicated that crops sowed at the time predicted by the AI-based app lead to 30% higher yields in the targeted geographical location.

Microsoft India has extended this further and uses AI & machine learning to assess the risk of pest attacks on crops. This helps farmers take preventive action before it is too late. On the other end of the spectrum, makers of predictive AI tools have even reached out to governments and policymakers through their price forecasting feature for agricultural goods.

Automating Tasks
The World Urbanization Prospects report a massive movement of population from rural to urban areas, thus leaving fewer hands-on-deck in the rural areas where agriculture thrives. This creates a need for automation of tasks that were previously manual.

Using automation AI-based tools that help operation through remote locations, agricultural operations can rely lesser on manual efforts in their processes such as driver-less tractors and automated irrigation systems that account for weather conditions.

Image Recognition Tools
Through image recognition, certain AI-apps have been developed that identify potential defects and certain deficiencies in the soil that’s easily captured by any smartphone. This app is called Plantix and has been developed by a Berlin-based start-up called PEAT. Once these deficiencies are found out, the farmers are then equipped with solutions such as soil restoration techniques and more so as to address the issue found. 

What’s Next?
Thanks to the success of AI-driven modifications in the farming sector in India, the path has been forged and is followed by plenty of upcoming technologies. The challenge is to reduce costs so as to make it marketable in a mass way. It is predicted by technology experts that crop and soil monitoring techniques will remain important tools even as climate change is being increasingly studied and documented.  

The tools currently seek to address the core issues in the agricultural sector such as crop yield increase, soil health, and pest prevention. It is even anticipated that AI robots might soon start making an impact in this sector.
While there is significant progress, the ground is fertile for newer technologies to take root in the Indian home soil of agriculture.

AI its usage to manage regulatory compliance in banking Fin Services!

Posted on by Imarticus Learning

A recent study revealed that the estimated annual cost of regulatory compliance and governance software spend by our banks is around $70 billion. Bank attorneys, loan officers, and paralegals spend thousands of hours into loan agreements, regulatory compliance filings, and other contracts to see if they comply with the law. Artificial Intelligence or AI has found its latest application in this significant issue among bankers. We are looking at a whopping 30% reduction in the total cost with this AI application.

How AI Helps…

The AI-based systems are now being implemented to document verification. They have been successfully tested to interpret regulatory meaning, comprehend the required action, and codify the compliance rules. The Contract Intelligence (COIN) programme developed by JPMorgan Chase is an example of the early adoption of AI technology. Through this system, the company can process loan documents that would cost around 360,000 working hours.

Some other areas of compliance services where AI can offer more safety are the following.

  • Know Your Customer – It’s already clear that AI systems can analyze a vast amount of data and scrape the web to find patterns. This ability can be used to strengthen the KYC processes. Pattern recognition techniques paired with unstructured text analysis, these systems can identify risk-prone customers.
  • Money Laundering Detection – Using AI, monitoring reports and regulatory alerts can be evaluated as risk indicators. The accounts with more significant exposure to these indicators can be analyzed further. It reduces the complexity of the existing Anti Money Laundering systems.
  • Detection of Rogue Employees – It is possible to find the employees who generate a fake account using AI. Reports using the same e-mail or IP address can easily be tracked down by AI.
  • Trade Monitoring – AI can learn about the trader’s behavior and personality. This will lead to more precise predictions about suspicious trading. The time lost due to false alarms can be saved.

More and more application of AI in financial regulatory compliance can be expected with the progress in the algorithmic machine learning models.

Challenges In Implementing AI

Regardless of the immense pros, few issues are slowing down the AI implementation. The problem of rectifying information processed by AI is considered one of the biggest. We know that often our internet can be riddled with fake news and misinformation. If such information gets to the AI and influences its decision, the result would be terrible.

The efficiency offered by AI in decision making is tremendous but, it also takes the professionals away from this decision making process. It may create an opacity for the regulators to see if the proper procedure is being followed for business practices such as suspicious activity reporting.

Despite these challenges, the potential offered by the AI is attracting the financial Institutes to try it. With researches showing large signs of progress day by day, we can expect AI to decode these challenges sooner. Shortly, the AI will undoubtedly replace the legacy system and reduce massive costs incorporated with the current system.