CNI Research Ltd Management Discussions

Industry Structure and Development

Tomorrow Technologies Global Innovations Limited is Artificial Intelligence (AI) company can be broadly categorized into several key areas. These reflect the ways AI is developed and applied across industries

1. Machine Learning (ML)

• Training algorithms on data to make predictions or decisions.

• Subfields:

o Supervised Learning (e.g., spam detection)

o Unsupervised Learning (e.g., customer segmentation)

o Reinforcement Learning (e.g., game-playing agents, robotics)

2. Natural Language Processing (NLP)

• Understanding and generating human language.

• Examples:

o Chatbots and virtual assistants o Language translation

o Sentiment analysis

o Text summarization

3. Computer Vision

• Enabling machines to “see” and interpret visual data.

• Examples:

o Facial recognition

o Image classification

o Object detection in videos or images

o Medical imaging analysis

4. Robotics and Automation

• AI applied to physical machines or systems.

• Examples:

o industrial robots

o Self-driving vehicles

o Drones

o Service robots (e.g., in healthcare or hospitality)

5. Expert Systems and Decision Support

• Rule-based systems that simulate human decision-making.

• Examples:

o Fraud detection systems o Medical diagnosis tools

o Legal or financial advisory systems

6. Generative AI

• Creating new content such as text, images, code, or music.

• Examples:

o Text generation (e.g., ChatGPT)

o Image generation (e.g., DALL-E)

o Code writing (e.g., GitHub Copilot)

7. AI Ethics and Safety

• Ensuring responsible development and deployment of AI.

• Activities:

o Bias detection and fairness

o Transparency and explainability

o Privacy preservation

o AI governance frameworks

Risks and Concerns

1. Job Displacement and Economic Disruption

Automation could replace millions of jobs (e.g., in transport, manufacturing, customer service). Creates uncertainty about the future of work and skills mismatch.

May increase inequality if benefits of AI are unevenly distributed.

2. Bias and Discrimination

AI systems can reflect or amplify biases in training data, leading to unfair outcomes in:

Hiring

Lending

Law enforcement Healthcare

Examples: facial recognition inaccuracies, biased language models.

3. Lack of Transparency (“Black Box” Problem)

Many AI models (especially deep learning) operate in ways that are hard to understand or explain. Makes it difficult to audit, trust, or hold systems accountable, especially in high-stakes decisions.

4. Privacy Invasion

AI systems often require vast amounts of personal data.

Used in surveillance, targeted advertising, and behavioral tracking.

Raises ethical and legal concerns around data use and consent.

5. Security Risks

AI can be used to:

Generate deepfakes or disinformation.

Launch more sophisticated cyberattacks.

Create autonomous weapons or tools for authoritarian control.

6. Misuse and Malicious Use

AI is dual-use: the same tools can be used for both good and harm.

Risks include:

AI-generated fraud or scams (e.g., voice cloning)

Automated hacking

Propaganda bots spreading misinformation.

7. Lack of Regulation and Oversight

Technology is advancing faster than governance.

Theres no global consensus on how to regulate AI.

Risk of regulatory gaps that allow harmful uses to go unchecked.

8. Existential Risks (Long-term concern)

Some experts warn of risks from future superintelligent AI that could act in ways harmful to humanity.

Debate continues on how close or real this risk is, but its a concern among AI safety researchers.

Internal control system and their adequacy

The auditors are reviewing the control systems and processes in the operations of the company. The Audit committee and the Board are reviewing the findings of the Auditors.

Discussion of financial performance with respect to operational performance

During FY 2025, your company reported a total revenue of Rs. 444.19 Lakhs. Your company is heavily dependent on stock markets. LTCG has resulted in nervousness in capital markets in the recent few quarters. Looking ahead, we believe the stock markets are expected to witness continuous uptrend in the long-term supported by optimism over key structural reforms which would further drive our profits in the sale of shares business segment.

Indian Govt has projected exports to reach 600 Bn $ by 2030 from current 44 bn $ which is 16x. this means capital market will prosper till 2030 and our estimate nifty 47000 will see the light of the day.

The chart below shows revenue growth and net profit performance of your company in last five years:

With a vision to boost reforms and promote investments in the country, the current NDA government unveiled Make in India programme in September 2014. Other objectives include building world class manufacturing infrastructure, improving the skill set of the Indian workforce, nurturing innovation and protecting intellectual property. It is estimated that electronics demand would reach $400 billion by 2021. With Make in India, the Government aims to bring down the electronics import by 2021 and strive towards becoming an electronic manufacturing hub. To develop a competitive edge in the world, the Government has identified 25 key sectors as a part of Make in India programme including Automobiles, Aviation, Defense Manufacturing, Oil and Gas, Tourism, etc. With this regard, there have been sector specific measures announced to attract domestic and foreign investors.

Some key features related to the Make in India programme:

New Initiatives: The government has taken varied steps to improve ease of doing business in India by simplifying business processes and procedures, opening up the economy through new de-licensing and deregulation measures and creating confidence among entrepreneurs through lesser turnaround time and creating transparency in the system. Indias rank in ease of doing business index has risen from 130th in FY 2017 to 100th in FY 2018. Some other reforms to create a healthier environment for businesses are: a) online portals for clearances and filings, b) launching the Indian Trade Portal and c) creating Investor Facilitation Cell for guiding investors through the entire life-cycle of the business.

Foreign Direct Investment (FDI): With an intent of creating a robust business environment, the government of India has relaxed norms for FDI in most of the sectors. FDI limit in the defence sector and railway infrastructure increased to 100% post the Make in India campaign. Substantial ease in FDI norms should be a key positive for the Indian economy as it should gain access to global economy and capital.

Intellectual Property Facts (IP): Changes were announced at legislative and policy level to protect intellectual property rights of innovators and creators by the government.

National Manufacturing: The major initiatives regarding this reform are: a) to raise the annual growth of manufacturing sector between 12% and 14% over the medium term, b) increasing share of manufacturing sector in GDP from 16% to 25% by 2022, c) to create around 100 million more jobs in the manufacturing sector by 2022 and d) developing skills of the rural population and urban poor.

The Make in India programme is gaining the confidence of domestic and global corporates which are willing to invest in India and the government has started to get proposals regarding the same.