Artificial Intelligence in Businesses Decision Making

Abstract

Artificial Intelligence (AI) has become a fast-growing force that is reshaping how many industries work, and business is one of the clearest examples. Firms are adopting AI to increase efficiency, improve customer experience, and gain a competitive advantage. This paper makes one central argument: AI genuinely improves business decision-making by turning large amounts of data into faster, more accurate and more consistent decisions, but only when a firm first meets real prerequisites (reliable data, adequate infrastructure, legal compliance and digital readiness), and only when governments regulate its use so that those decisions stay fair, transparent and safe. It examines the advantages of AI in decision-making, the ethical and workforce risks it creates, and the regulatory steps, especially in India, needed to manage them.

Introduction

Artificial intelligence is a group of technologies that let computers perform advanced tasks such as machine learning, data analytics and natural language processing, allowing these systems to imitate aspects of human intelligence. In business, AI gives organisations advanced analytical capabilities, helping them extract useful insights from vast amounts of data. It can also carry out tasks such as forecasting and trend analysis while saving time, money and effort. Many businesses have already begun using AI to streamline operations, speed up turnaround times and boost productivity.

Technology is currently evolving at an unprecedented rate, and AI is quickly becoming a standard business tool rather than an experiment; firms that adopt it early are positioning themselves for a competitive advantage. However, as businesses integrate AI into their decision-making, several challenges must be addressed. Data privacy and security concerns arise because AI relies on large amounts of sensitive information. Ethical considerations, the responsible, transparent and non-discriminatory use of AI, must be managed so that automated decisions align with societal values. Finally, the effect on the labour force matters: because AI can automate parts of some jobs, workers may need reskilling or upskilling, and existing roles may change.

Literature Review

To ground this argument, this section reviews what researchers and institutions have actually found about AI and decision-making.

Productivity and decision-making

Analysts at McKinsey estimate that generative AI alone could add the equivalent of $2.6 trillion to $4.4 trillion to the global economy each year, with about three-quarters of that value concentrated in customer operations, marketing and sales, software engineering, and research and development (McKinsey, 2023). A field study of a Fortune 500 firm's customer-support centre found that giving agents an AI conversational assistant raised the number of issues they resolved per hour by about 14% on average, with the largest gains, over 30%, among the newest and least-experienced workers (Brynjolfsson, Li & Raymond, 2023). These are exactly the faster, more accurate and more consistent decisions that businesses hope AI will deliver.

Fraud detection and financial operations

AI is also a powerful tool for risk assessment and fraud detection. The U.S. Treasury reported that machine-learning systems helped it prevent and recover more than $4 billion in fraudulent and improper payments in fiscal year 2024, including about $1 billion in check fraud, up roughly six-fold from $652.7 million the year before (U.S. Treasury, 2024). This shows how AI can process huge transaction volumes and flag suspicious patterns far faster than manual review.

E-commerce and personalisation

In retail and e-commerce, AI improves how firms recommend products and manage stock. Amazon, for example, uses recommendation systems that analyse a customer's browsing and purchasing history to generate personalised product suggestions, and uses demand forecasting to predict which products will be needed and when, helping it avoid overstocking or understocking and cut costs. McKinsey's analysis identifies marketing, sales and customer operations as the areas where AI creates the most value (McKinsey, 2023), which fits this pattern. At the same time, this reliance on customer data makes privacy, transparency and accountability critical concerns.

The speed of adoption is striking. Consumer technology shows how quickly AI has gone mainstream: when Samsung unveiled its Galaxy S24 series on 17 January 2024, the phones shipped with built-in "Galaxy AI" features such as real-time call translation and a "Circle to Search" tool (Samsung, 2024).

Workforce impact

Finally, a widely cited study by the International Monetary Fund found that almost 40% of global employment is exposed to AI, including many high-skilled jobs. In advanced economies about 60% of jobs are exposed; roughly half of those could benefit from higher productivity, while the other half may face lower labour demand, reduced hiring, or in extreme cases job losses. Exposure is lower in emerging markets (about 40%) and low-income countries (about 26%), which means fewer immediate disruptions but a real risk of widening inequality over time as adoption spreads (IMF, 2024).

The Role of Artificial Intelligence in Business Decision-Making

AI's role in business keeps growing, and it is steadily changing industries one by one. It can be used for many purposes, from spotting data trends that reduce market risks to improving customer service through AI assistants. It is useful across departments, finance, human resources and marketing, and its consistent, rule-based processing can help reduce human error, freeing a business to focus on growth.

Decision-making is central to running a business. Some decisions can only be made after carefully reviewing the relevant facts or trends, financial decisions, for example. AI-supported decisions let companies act faster and more consistently, because the system can weigh far more data than a person can in the same time. In a sense, human and machine decision-making sit close together: a manager draws on experience, while an AI draws on historical data. For AI, data is the essential ingredient, without good data, it cannot produce reliable decisions. Used well, AI supports more focused decision-making while saving time and money, and it can also handle data collection, forecasting and trend analysis.

What a Firm Actually Needs Before Adopting AI

AI does not create value automatically. A firm can only benefit from it after meeting several concrete prerequisites. What earlier drafts loosely called an "Electronic Internet Business plan" is better understood as a clear AI-readiness plan covering four things:

• Data readiness. AI systems improve with more and better data. Businesses generate large amounts of data every day, but it must be accurate, well-organised and relevant before it can be used to train models or generate insights. Poor-quality data leads to poor decisions.
• Infrastructure and cost. Running AI well requires computing power, software and often cloud services. As the evidence below shows, this can be expensive, so a firm needs a realistic budget and technical setup before it starts.
• Legal and compliance framework. Because AI relies on personal and sensitive data, a firm must comply with data-protection law, in India, the Digital Personal Data Protection Act, 2023 (discussed below). Clear rules on how data is collected, stored and used are a prerequisite, not an afterthought.
• Digital transformation and goals. Adopting AI usually changes how departments work, from retail operations to human resources. A firm needs defined goals for what the AI should achieve and a plan for how teams and processes will adapt.

Sectors that depend heavily on data and prediction, banks and real estate, for example, stand to gain the most, because AI-generated insights can give them an edge over competitors. But that edge only appears once these prerequisites are in place.

Evidence: How Far AI Has Spread, and What It Delivers

How widely is AI actually used? McKinsey's Global AI Survey found that the share of organisations that had embedded at least one AI capability into a process or product rose from 47% in 2018 to 58% in 2019, a clear upward trend even before the generative-AI boom (McKinsey, 2019). Adoption has continued to climb since.

What does AI deliver, and at what cost? The evidence above points to real gains: measurable productivity improvements in customer support (Brynjolfsson, Li & Raymond, 2023), billions of dollars in fraud caught (U.S. Treasury, 2024), and large potential economic value concentrated in customer-facing functions (McKinsey, 2023). But those gains come with a genuine cost. Running AI smoothly requires investment in infrastructure and skilled staff, and most organisations must go through a digital transformation that changes how departments operate before the benefits appear. AI is therefore not a quick fix; it is an investment that pays off only when the prerequisites in the previous section are met.

Impact on Business: Customers and Strategy

One of the most valuable capabilities of an AI system today is managing customer relationships. In sales and marketing, AI can gather data about customers and use it to improve the products and services a company offers, and to raise customer satisfaction. Used successfully, AI can change how an organisation operates and sets strategy, and it encourages closer collaboration between managers and machines, with people providing goals and judgment, and AI providing scale and speed.

Regulating AI in Business Decisions: India's Emerging Framework

When this paper's argument is applied to India, the key question is how the government should regulate AI used in business decisions. India does not yet have a single, dedicated AI law, but the claim that there are "no laws" is no longer accurate. Several frameworks already apply:

• The Digital Personal Data Protection Act, 2023 (DPDP Act) governs how organisations handle digital personal data. It contains 44 sections across nine chapters and applies not only to data processed in India but also to processing done outside India when it is connected to offering goods or services to people in India (Government of India, 2023).
• The IndiaAI Mission, approved by the Union Cabinet in March 2024 with an outlay of about ₹10,371 crore, funds AI computing capacity, datasets, skilling and safe-AI research (Government of India, 2024).
• On 5 November 2025, the Ministry of Electronics and Information Technology (MeitY) released India's AI Governance Guidelines, which favour a light-touch, adaptive and risk-based approach that builds on existing laws rather than a rigid new statute, guided by a "do no harm" principle (MeitY, 2025).

Building on this foundation, the government could take the following concrete steps to regulate AI in business decision-making:

1. A mandatory AI ethics code for businesses that requires AI systems to be built and used in ways that are fair and non-discriminatory.
2. Regular AI impact assessments, requiring firms to test their AI systems for ethical implications and possible risks.
3. Targeted additions to the DPDP Act, for example, specific rules on how businesses collect, store and use personal data inside AI applications, and a clearer mandate for appointing Data Protection Officers to oversee compliance.
4. Disclosure requirements, so businesses clearly state when AI is used in decision-making, especially in customer-facing services.
5. Industry-specific safety standards for high-stakes AI applications, with particular emphasis on healthcare and finance.
6. Clear liability rules, so that companies are held responsible for the outcomes of their AI systems.

Handled well, this kind of regulation does more than protect the public; by building trust, it can encourage responsible adoption, support new jobs in AI and compliance, and strengthen the wider economy.

Conclusion

Artificial intelligence is a transformative force in business decision-making, and it is clearly a major part of the future. By using AI systems to analyse vast amounts of data and generate predictions and suggestions, businesses can make better, faster and more consistent decisions, and many have already started doing so to improve their strategies. But the evidence in this paper points to two conditions for success. First, a firm must meet real prerequisites, reliable data, adequate infrastructure, legal compliance and a plan for change, before AI delivers value. Second, governments must regulate AI's use so that automated decisions remain fair, transparent and safe. In India, the DPDP Act, the IndiaAI Mission and the 2025 AI Governance Guidelines are early steps; the challenge now is to turn them into clear, enforceable rules for AI in business. Managed this way, AI can genuinely improve how businesses decide, without undermining the public interest it is meant to serve.

Sources

1. International Monetary Fund (2024). AI Will Transform the Global Economy. Let's Make Sure It Benefits Humanity. imf.org
2. McKinsey & Company (2023). The economic potential of generative AI: The next productivity frontier. mckinsey.com
3. Brynjolfsson, E., Li, D., & Raymond, L. (2023). Generative AI at Work. NBER Working Paper 31161. nber.org
4. U.S. Department of the Treasury (2024), as reported by Nextgov/FCW. AI tools helped Treasury recover billions in fraud and improper payments. nextgov.com
5. McKinsey & Company (2019). Global AI Survey: AI proves its worth, but few scale impact. mckinsey.com
6. Government of India (2023). The Digital Personal Data Protection Act, 2023. India Code. indiacode.nic.in
7. Government of India (2024). Union Cabinet approves IndiaAI Mission with ₹10,371 crore budget. DD News. ddnews.gov.in
8. Ministry of Electronics and Information Technology (2025). MeitY unveils India AI Governance Guidelines. News on AIR. newsonair.gov.in
9. Samsung (2024). Highlights From Galaxy Unpacked: The Promise of a New Beginning With Galaxy AI. Samsung Global Newsroom. news.samsung.com