For better or worse, artificial intelligence has now entered the mainstream and will likely proliferate across most industries over the short term. This is an opportunity to make money or secure a competitive advantage.
With cyberattacks becoming more frequent and complex, the importance of AI in threat detection is becoming increasingly important. AI is also useful in home management as more consumers with more devices and soaring energy costs look for solutions.
AI businesses can also be started in customer support, marketing, and sales where trained models can automate tedious tasks or those with a low ROI. This frees up people to concentrate on tasks that directly impact the company’s bottom line.
For better or worse, artificial intelligence has now entered the mainstream and will likely proliferate across most industries over the short term.
The shift toward this new era represents a significant opportunity for businesses to not only make money but also secure an advantage over their competitors.
How can this be achieved, exactly? Below, we’ve taken the liberty to list just a few of the numerous (and viable) AI business ideas available today.
With cyberattacks becoming more frequent and complex, the importance of AI in threat detection is becoming increasingly important.
AI can detect and identify anomalous patterns and vulnerabilities in extensive networks. It can also rapidly analyze vast datasets from multiple endpoints to prevent some threats before an attack is executed.
In essence, AI is a way for companies to maintain pace with the constant evolution of cyber attacks. Over time and as more data is analyzed, it learns from experience and becomes more capable of responding to threats than the traditional software-driven approach.
Home management
There is also potential to profit from the proliferation of electronic devices that now occupy the average home. Businesses in this sector offer AI that enables homeowners to manage their devices with the simple press of an app.
What’s more, many consumers are turning to AI-powered solutions to reduce their energy consumption amidst soaring costs. Electricity trading, intelligent power consumption, and energy storage facilitation are all arenas in which AI is useful.
Customer support
Some aspects of customer support consume time and money that could be better spent elsewhere. Demand for customer support is also unpredictable. The team may be overstaffed one day and then understaffed the next.
Fortunately, AI can be used to handle many customer support requests. Some tools can detect the tone, purpose, and context of the message before sending it to the relevant team. Other tools have analyzed thousands of prior conversations to learn words that indicate urgency or interest and respond accordingly.
Marketing and sales
With advanced data and long-term expertise, artificial intelligence can also be used to sell services that predict or optimize the success of marketing campaigns. It can also strike the correct balance between operational efficiency and customer experience. One particular application of AI in marketing is computer vision, which can be used to infer meaning from millions of images, videos, and other inputs to identify trends or clarify how products and services are used.
The benefits of AI in sales are enormous. Research from the Harvard Business Review found that companies that incorporated AI into sales saw a 50% increase in leads and a 60-70% reduction in call time. With people able to spend more time on important tasks such as closing deals, AI also reduced total costs by as much as 60%.
Key Highlights
Opportunities in AI Business Ideas:
The mainstream integration of AI offers businesses a chance to gain a competitive edge and generate revenue.
Several viable AI business ideas exist in various sectors, including cybersecurity, home management, customer support, and marketing.
AI’s ability to detect threats and vulnerabilities in extensive networks is crucial for enhanced cybersecurity.
Home management AI solutions cater to the increasing number of electronic devices in homes, enabling efficient device control and energy consumption optimization.
AI-powered customer support tools can handle various tasks, such as analyzing message context and sentiment, leading to improved efficiency and reduced costs.
AI contributes to successful marketing campaigns by predicting outcomes and optimizing strategies. It also aids in understanding consumer behavior through computer vision technology.
Cybersecurity:
AI’s role in threat detection is vital due to the rising frequency and complexity of cyberattacks.
AI can analyze vast datasets from multiple endpoints, identifying anomalies and preventing attacks.
Machine learning allows AI to learn from experience, improving its response to evolving threats.
Home Management:
AI solutions for home management are in demand as households increasingly incorporate electronic devices.
Homeowners use AI apps to control devices, manage energy consumption, and optimize energy storage.
The need for AI-based home management solutions is fueled by remote work and rising energy costs.
Customer Support:
AI-powered customer support tools handle requests, saving time and money.
AI analyzes message tone, context, and urgency to route inquiries effectively.
Automated responses based on analyzed conversations enhance customer experience and support efficiency.
Marketing and Sales:
AI enhances marketing and sales efforts by predicting campaign success and improving operational efficiency.
Computer vision technology assists in understanding consumer behavior by analyzing visual data.
AI integration in sales processes leads to increased leads, reduced call times, and overall cost savings.
Impact on Business Bottom Line:
Incorporating AI in business tasks with low ROI automates repetitive and time-consuming processes.
AI tools enable employees to focus on critical tasks that directly contribute to the company’s success.
Companies that implement AI in sales and other areas experience significant improvements in leads, call times, and cost reduction.
Generalized AI consists of devices or systems that can handle all sorts of tasks on their own. The extension of generalized AI eventually led to the development of Machine learning. As an extension to AI, Machine Learning (ML) analyzes a series of computer algorithms to create a program that automates actions. Without explicitly programming actions, systems can learn and improve the overall experience. It explores large sets of data to find common patterns and formulate analytical models through learning.
Machine learning is a subset of artificial intelligence where algorithms parse data, learn from experience, and make better decisions in the future. Deep learning is a subset of machine learning where numerous algorithms are structured into layers to create artificial neural networks (ANNs). These networks can solve complex problems and allow the machine to train itself to perform a task.
DevOps refers to a series of practices performed to perform automated software development processes. It is a conjugation of the term “development” and “operations” to emphasize how functions integrate across IT teams. DevOps strategies promote seamless building, testing, and deployment of products. It aims to bridge a gap between development and operations teams to streamline the development altogether.
AIOps is the application of artificial intelligence to IT operations. It has become particularly useful for modern IT management in hybridized, distributed, and dynamic environments. AIOps has become a key operational component of modern digital-based organizations, built around software and algorithms.
Machine Learning Ops (MLOps) describes a suite of best practices that successfully help a business run artificial intelligence. It consists of the skills, workflows, and processes to create, run, and maintain machine learning models to help various operational processes within organizations.
OpenAI is an artificial intelligence research laboratory that transitioned into a for-profit organization in 2019. The corporate structure is organized around two entities: OpenAI, Inc., which is a single-member Delaware LLC controlled by OpenAI non-profit, And OpenAI LP, which is a capped, for-profit organization. The OpenAI LP is governed by the board of OpenAI, Inc (the foundation), which acts as a General Partner. At the same time, Limited Partners comprise employees of the LP, some of the board members, and other investors like Reid Hoffman’s charitable foundation, Khosla Ventures, and Microsoft, the leading investor in the LP.
OpenAI has built the foundational layer of the AI industry. With large generative models like GPT-3 and DALL-E, OpenAI offers API access to businesses that want to develop applications on top of its foundational models while being able to plug these models into their products and customize these models with proprietary data and additional AI features. On the other hand, OpenAI also released ChatGPT, developing around a freemium model. Microsoft also commercializes opener products through its commercial partnership.
OpenAI and Microsoft partnered up from a commercial standpoint. The history of the partnership started in 2016 and consolidated in 2019, with Microsoft investing a billion dollars into the partnership. It’s now taking a leap forward, with Microsoft in talks to put $10 billion into this partnership. Microsoft, through OpenAI, is developing its Azure AI Supercomputer while enhancing its Azure Enterprise Platform and integrating OpenAI’s models into its business and consumer products (GitHub, Office, Bing).
Stability AI is the entity behind Stable Diffusion. Stability makes money from our AI products and from providing AI consulting services to businesses. Stability AI monetizes Stable Diffusion via DreamStudio’s APIs. While it also releases it open-source for anyone to download and use. Stability AI also makes money via enterprise services, where its core development team offers the chance to enterprise customers to service, scale, and customize Stable Diffusion or other large generative models to their needs.
Gennaro is the creator of FourWeekMBA, which reached about four million business people, comprising C-level executives, investors, analysts, product managers, and aspiring digital entrepreneurs in 2022 alone | He is also Director of Sales for a high-tech scaleup in the AI Industry | In 2012, Gennaro earned an International MBA with emphasis on Corporate Finance and Business Strategy.
