For the past decade, AI has become a core feature in many of the products and services we use. With the breakthrough of huge foundational models, innovators are seeing new ways to make machine interactions more human. Let me take a step back and provide some background.
Artificial intelligence is this big umbrella that covers machine learning. Many of the predictive algorithms we are familiar with in our platform services leverage complex machine learning algorithms to understand our personal preferences better. While there are subtly different definitions of AI in literature, I think that our current innovation trends match my definition of AI closer than the predictive algorithms we are familiar with. The definition of AI I like the most is “a field of computer science that focuses on developing machines that can perform tasks that are normally associated with human intelligence.” The core part of this definition being the aim to bring machines closer to human intelligence. This is where the innovation space is most exciting to me. Businesses are building teams to better understand what AI integrations mean and look like for business success.
Innovation leaders have already found ways to include AI in business operations. From automating repetitive tasks to enhancing decision-making through data analytics, AI is quickly becoming a cornerstone of modern business strategy. As we look toward the future, it’s clear that AI will continue to reshape how businesses operate. I’ve compiled what I think are the five most common ways companies incorporate AI into their business operations.
- Automation: In manufacturing, AI-powered robots are automating tasks like assembly, quality control, and even packaging. For instance, companies like Amazon have streamlined their warehouses with AI-powered robots that can pick and pack orders more efficiently than humans. We’ve also come to accept that interactions with customer service will often start with an automated system. AI-driven chatbots handle routine inquiries by phone or email, freeing up human agents for more complex issues.
- Data Analytics: Companies have millions of data points for their customers, and many have found ways to use AI to find trends and patterns in the data that may lead to improvements in user experience or efficiencies in business operations. AI algorithms can comb through vast datasets to find patterns humans might miss. Companies like TikTok use AI to analyze user behavior and push personalized content suggestions to keep users engaged with the platform, boosting revenue.
- Customer Experience: Data Analytics is more of a behind-the-scenes approach to the customer experience. Some AI features are more customer-facing. Chatbots and virtual assistants are systems that customers can engage with at any time. With more companies looking to include foundational models in their chatbots, I anticipate that virtual assistants will be able to better answer the questions we ask it.
- Supply Chain & Logistics: I’ve also seen companies invest in AI factories. Execs see value in leveraging AI to optimize manufacturing and supply chain processes by predicting demand, managing inventory, and planning more efficient delivery truck routes. FedEx, for example, uses AI to predict package delivery times more accurately, ensuring smoother logistics operations.
- Risk Management: Companies are increasingly using AI to identify and mitigate risks across the business. So far, we have talked about how AI is great at identifying patterns in data. On the flip side of the same coin, AI is also great at detecting anomalies in the data. For example, financial institutes leverage machine learning to detect fraudulent activity and predict the likelihood of loan defaults.
I know that LLMs will improve the existing use cases. I also anticipate businesses finding new ways to include AI in business strategy and operation. Knowing the capabilities of this technology, let’s go crazy. Maybe in the future, AI will…
- Augmented the Workforce: Rather than replacing human workers, AI will increasingly serve as a tool to augment their capabilities. It will be increasingly more common for people to elicit an AI assistant’s help to make data-driven decisions.
- Make Knowledge Sharing Easier: Companies have large internal knowledge databases, and sometimes, finding the information you want can be challenging. Rather than messaging colleagues hoping someone can take time out of their busy schedule to help you with your work, imagine having a virtual assistant to help locate the information you seek.
- Automate Project Management: Imagine having an AI assistant to help manage your calendar. Based on a project’s progress, the assistant will be able to see the pipeline in full transparency and pencil in necessary team meetings, anticipating when people will want to reconvene for standup meetings.
Many possible use cases exist, but I don’t want to be too dystopian. I think the possibilities are infinite, but not all ideas are good. More so than ever, it is vital to consider how people will be impacted by these technologies. Will people feel that companies are invading privacy? Will the technology feel like people are being micromanaged? Is the business using AI responsibly? While companies focus a lot on AI capabilities, it is also essential to highlight the challenges and ethical considerations businesses must address. I’ll have to write another blog post on responsible AI, or this post will go on forever. So let’s put that conversation on hold and continue the conversation to how AI might fundamentally change how businesses are run.
The future of AI in business isn’t just about improving existing processes; it’s about reimagining business. AI has the potential to be a disruptive force, much like the rise of social media. When social media platforms emerged, they reshaped entire industries by creating platform-based business models that connected service providers with users in new ways. Similarly, AI could drive a new wave of business innovation, unlocking entirely different models built around intelligent systems and automation.
While it’s impossible to predict the future, we can see two types of AI businesses now.
- AI native businesses like OpenAI
- AI-as-a-Service businesses like Amazon and Microsoft.
Most businesses that aren’t trying to compete with OpenAI and the other tech powerhouses in building the best foundational models are leaning towards offering their AI products as a procurable service. These companies specialize in creating AI-driven solutions that can be easily integrated into other businesses’ operations. While at HBS, I chatted with a design consulting firm that had transformed its business with AI. He explained that their projects were moving much faster due to AI disrupting their traditional billable-hour model. Recognizing that AI allowed their consultants to deliver high-quality results in a fraction of the time, they shifted to offering AI-enabled services at an additional cost. He said that his consulting firm business model now functioned more like a software-as-a-service model.
I know we are on the cusp of another AI breakthrough in business. Companies are navigating the shift from traditional business models to ones that leverage AI for faster, smarter solutions. I hope this post sheds some light on the exciting transition we are witnessing and the new opportunities it brings for innovation in business strategy and operations.