The Impact of AI and Automation on Investing in 2025

 

In 2025, artificial intelligence and automation are expected to play a major role in the world of investing. From smarter decision-making to faster trade execution, these technologies are changing how portfolios are managed and how investors approach the market.

How Do Businesses Use AI?
Companies apply AI in various ways to enhance efficiency. For instance, AI can handle routine tasks such as sending notifications or managing spreadsheet updates. By integrating AI into existing systems, businesses can streamline operations and boost overall performance.

AI-powered scheduling tools, for example, can automatically arrange appointments, organize meetings, and send confirmations—completely hands-free. It’s a straightforward and effective solution.

How AI Automation Can Benefit Your Business

Streamlining Repetitive Tasks:
Many day-to-day business activities are time-consuming and repetitive. With AI, tasks like order processing, email management, and payment tracking can be automated, freeing up employees to focus on higher-value work. This is where automation brings real efficiency to business operations.

Enhancing Decision-Making:
AI also supports smarter business decisions by analyzing data to uncover trends and patterns. It can forecast customer behavior or suggest ways to boost sales, offering valuable insights that help businesses plan ahead more effectively.

 

 AI Reasoning and Custom Silicon Drive Chip Demand
AI reasoning is a major contributor to the growing need for computing power and, in turn, semiconductors, according to chip industry leaders. Unlike basic AI tasks, advanced reasoning involves deeper learning and decision-making processes, which significantly increases computing requirements for stages like pre-training, post-training, and inference.

Executives also noted their ongoing investments in infrastructure to support custom data-center designs. These include enhancements in memory, power efficiency, and the development of custom silicon tailored for specific AI workloads rather than relying on general-purpose chips. There is ongoing debate among customers about whether to adopt application-specific integrated circuits (ASICs), which deliver higher efficiency and performance for particular tasks, versus more versatile general-purpose GPUs. The demand for ASICs is expected to grow, especially as edge AI applications become more prevalent in smaller devices over the next few years.

Enterprises Eye AI Reasoning as the Next Big Leap for LLMs
The creators of the largest language models are aiming to combine top-tier hardware with advanced software to deliver AI solutions that become indispensable to both businesses and consumers. While initial applications of LLMs focused on tasks like content creation, summarization, and classification, executives believe the greatest yet-to-be-fully-realized value lies in applying AI reasoning to enterprise data.

Currently, businesses are leveraging LLMs for customer service bots, internal data search, marketing content, code generation, and business analytics. However, AI reasoning could elevate this by enabling smarter, context-aware suggestions, deeper data insights, streamlined operations, regulatory compliance, and strategic decision-making. Industry leaders anticipate rapid progress in areas like coding efficiency, with one noting that a single developer’s productivity may have increased tenfold. Sectors such as biotechnology—especially in clinical trials and compliance documentation—and legal services, through AI-assisted paralegal functions, are expected to be among the first to see dramatic gains from customized AI tools.

Data Companies Focus on Assessing AI Performance
Firms in the data and cloud infrastructure space are developing tools to help businesses automate observability gaining insight into system behavior through data analysisand to build AI evaluation systems that enhance return on investment.

AI has sped up coding significantly, but the real value now lies in testing, understanding, and determining its business impact,” said Enrique Perez-Hernandez, Head of Global Technology Investment Banking at Morgan Stanley. “Data companies are now creating AI solutions that help organizations assess whether large language models are functioning effectively and delivering business value.

Why Is Automation Becoming More Intelligent?
In the coming years, automation powered by artificial intelligence will significantly simplify operations for businesses. Tools like digital twins—virtual replicas of physical machines—will enable companies to anticipate and address issues before they occur, minimizing downtime and inefficiency. Additionally, AI will begin to handle routine tasks such as managing calendars and replying to emails, allowing businesses to operate more efficiently.

How Will This Impact Various Industries?
E-commerce:
Ever notice how online shops seem to know exactly what you want? That’s AI at work, analyzing your preferences to recommend products you'll likely purchase, which drives higher sales.

Manufacturing:
AI is being used to automatically inspect products for flaws, increasing accuracy and saving time.

Finance:
Banks and financial firms are leveraging AI to detect fraud by rapidly analyzing large volumes of transactions, helping to protect customers' money.

Overall, the future of business will be increasingly driven by AI and automation. Companies that embrace these technologies can expect enhanced efficiency, fewer errors, and improved customer satisfaction.

Getting Started with AI Automation

Step 1: Pinpoint Time-Intensive Activities
Begin by identifying which tasks in your business are consuming the most time. Are employees bogged down with repetitive work like answering routine customer inquiries or managing files? These are ideal candidates for AI automation. Targeting such areas can allow your team to focus on higher-value tasks.

Step 2: Collaborate with a Skilled AI Provider
Partnering with experts in AI makes the transition smoother. Choosing an AI provider who understands your industry can significantly improve outcomes—from enhancing customer support to optimizing operations. These professionals can recommend and implement the right AI tools tailored to your business needs, driving growth and efficiency.

Step 3: Start Small, Measure Results, and Scale Up
Begin by automating a single process and evaluate its performance using key performance indicators (KPIs). If the outcome is successful, gradually roll out automation to other areas. This step-by-step approach ensures your business sees real benefits before broader implementation.