How Artificial Intelligence and Machine Learning can be used for your project or work?

Course Discussions AI and ML for Managers
#102

AI/ML with natural language processing to ease access/queries to internal daashboards

#103

Hi,

I’m working in mapping industry and I believe ML can help to detect change in reality hence we can maintain map freshness which reflect with reality

Regards,
Triawan

#104

I work in financial instituion, where we are using AI/ML models can be used in the following cases

We receive notifications from other financial institutions like exchanges, despositories etc. Example, Change in exhange codes, symbols, trade settlement time etc. We receive close to 100 notifications in day (average) from other financial insitution. Right now, these notifications are manually read by an employee to understand the impact of the Change Notification. We can develop ML model, which would digest different notifications received and help to classify them as Impact/Non Impact notification

#105

Hi All,

I belong from healthcare recruitment sector, I would recommend using AI and ML in day to day manual activities we do on internal tools which can automated to reduce time and increase productivity. With the help of ML we will be able to identify the weeks or months where revenue is low and how we can work on converting those durations.

#106

In my work, I use AI and ML to make everyday tasks easier and more efficient. For example, I use machine learning to analyze customer feedback and spot trends, helping me decide on improvements faster. AI tools also automate routine tasks, so I can focus on creative problem-solving. This technology feels like a helpful partner that makes my work smoother and my decisions smarter.

Thanks
Sakshi Rai

#107

Hi,

I am working as a software tester. Right now we are not using AI or ML. But kept hearing about Gen AI, AWS. My thought about ML and AI in software testing could be used in test case creation, regression testing, automation test suite preparation etc.

The disadvantage could be testing the software as there could be frequent changes in functionality, UI.

#108

Hello All,

I work as Cybersecurity Architect in one of the MNC.

Introduction:
Below is the case study and I want to build a project, My company is Automation solution provider which is using AWS, Azure and GCP and On-premises solution to deliver the Client needs.

They help customers build automations and has to handle sensitive / PII Data and can experiencing a surge in cyberattacks, including sophisticated phishing attempts, ransomware, and attempted data exfiltration. Goal is to enable company to maintain adequate security posture for various clouds and on-prem solutions. Also provide proactive and intelligent approach to SOC and SecOps and cloud security teams.

Challenges:

  1. Since it’s a multiple cloud environments, we find it difficult to get candidates which has expertise in all CSPs.
  2. Security Service available in every cloud is different and finding a common solution or standard for all cloud is difficult.
  3. If we ingest all available cloud logs in SIEM, it has all the logs but building alert based on the logs to get a genuine security issue is difficult because of bulk of data.
  4. Threat landscape is increasing day by day, now with sophisticated and state sponsored attacks it’s becoming difficult to protect the infrastructure. So we need rapid and latest threat intel to build such protections.
  5. Vulnerabilities in the deployed code / library, OS or infra component can cause exploit, so performing Applicability analysis based on deployment is difficult.
  6. Obtaining Compliance certifications (GDPR, PCI DSS, HIPPA, HITRUST, SOC1, SOC2, ISO 27001/17/18, ISO 42001) needs readiness and evidence collection and happens every year or in two years can be tedious.

Solution:
We can utilize AI to overcome some of the above challenges and obtain enhanced security operations.

  1. AI Based CSPM:
  2. AI Based SIEM:
  3. AI Based Threat Intelligence:
  4. AI Based UEBA (User and Entity Behaviour Analytics):
  5. AI Based vulnerabilities triaging:
  6. AI Based Compliance Agent:
#109

Hi,

As Software Engineering Manager, one use case that I can think of is to potentially see the value in using AI-Powered code generation tools like GitHub copilot to assist developers. in writing code more efficiently, writing test cases, providing suggestions on best practices as well as code refactoring.

Thanks,
Deepu

#110

Hi,

In my role as a Technical Project Manager, I see potential value in AI-powered tools in predicting project timelines, assess risks, and suggest optimal project schedules based on historical data from similar projects. ML Algorithms could be used to analyze past projects to forecast delays, resource allocation and potential bottlenecks.

Using documentation summarization via NLP techniques, we could also figure out a way to reduce the time spent on manually reviewing and understanding large sets of project documentation.

Thanks,
Anju

#111

In my work, I plan to leverage AI/ML to drive innovation, improve efficiency, and enable smarter decision-making.
For instance, I could enable users to write English sentences to derive results from a database like Snowflake instead of running queries explicitly. This way, the solution could be exposed to non technical users as well.