[Parts of this article were generated with *ai* from OpenAI and Google.]
Winter is coming. The foaming news tech releases on *ai* are reaching a fevered pitch just before many of us shut down for the holidays. Gemini is unveiled to a “meh” reception from MIT. AMD shares forecasting data for their new “faster – cheaper” GPU engine and the stock drops 2%. .ai domains are being purchased by bots for nearly $2oo a pop, for a two-year domain registered to the country of Anguilla. It’s a gold rush and a grifter market. Get ready for *ai* cash apps, well, they’re already here.
What areas of business are going to see exponential value in *ai* investments in the next 24 months?
That question is better answered by an AI, don’t you think?
Predicting the future is always a tricky business, but based on current trends and advancements in artificial intelligence (AI), several types of businesses stand to gain significant benefits in the next 24 months:
1. Generative AI Businesses:
Content creation: Companies offering AI-powered solutions for generating text, music, images, and other creative content will likely see explosive growth. These businesses can automate routine tasks for creators, personalize content for individual users, and even generate entirely new forms of art and entertainment.
Software development: AI-assisted coding and no-code development platforms are rapidly evolving, allowing businesses to build software faster and more efficiently. These tools can automate repetitive tasks, suggest code snippets, and even generate entire applications based on user input.
Marketing and advertising: AI is already being used to personalize ad targeting, analyze customer behavior, and optimize marketing campaigns. In the next 24 months, expect to see even more sophisticated AI tools emerge, helping businesses achieve unprecedented levels of marketing effectiveness.
2. Automation and Robotics Businesses:
Manufacturing and logistics: Businesses that automate their production lines and supply chains using AI-powered robots and intelligent systems will gain significant efficiency and productivity advantages.
Customer service and support: Chatbots and virtual assistants powered by AI will become increasingly commonplace, providing 24/7 customer support and automating repetitive tasks.
Healthcare: AI-powered systems can assist with tasks like diagnosis, treatment planning, and surgery, improving patient care and reducing costs.
3. Data and Analytics Businesses:
Data management and analysis: Businesses that offer AI-powered tools for collecting, storing, and analyzing data will be in high demand. These tools can help businesses extract valuable insights from their data, improve decision-making, and identify new business opportunities.
Predictive analytics: AI can analyze historical data and trends to predict future outcomes with remarkable accuracy. Businesses that leverage predictive analytics can gain a competitive edge by anticipating customer needs, optimizing inventory management, and minimizing risk.
Cybersecurity: AI is increasingly being used to detect and prevent cyberattacks. Businesses that invest in AI-powered cybersecurity solutions will be better protected from evolving threats.
4. Cloud Computing and AI Infrastructure Businesses:
Cloud computing providers: Cloud platforms like Google Cloud Platform, Amazon Web Services, and Microsoft Azure offer a range of AI services and tools, making it easier for businesses to adopt and leverage AI technology.
AI chipmakers: Companies developing specialized AI chips, such as Nvidia and Intel, will be crucial for supporting the growing demand for AI computing power.
Data center and infrastructure providers: Businesses that build and operate the data centers and infrastructure needed to support AI applications will see increased demand for their services.
5. Businesses in Highly Personalized Industries:
Retail and e-commerce: AI can personalize the shopping experience for individual customers, suggesting relevant products, and optimizing product recommendations.
Financial services: AI can be used to provide personalized financial advice, detect fraudulent activity, and automate investment decisions.
Media and entertainment: AI can personalize content recommendations, create dynamic advertising experiences, and even generate new forms of entertainment tailored to individual preferences.
It’s important to note that these are just a few examples, and the landscape of AI is constantly evolving. The specific types of businesses that benefit the most will depend on various factors, such as the pace of technological advancements, industry adoption rates, and regulatory developments. However, one thing is certain: AI is poised to transform businesses across all industries in the coming years, and those who embrace this technology early will be poised for success.
I think ChatGPT might have a more seasoned response. Let’s check in with 3.5 Turbo, for a different AI.
I can provide you with some general trends and areas where artificial intelligence (AI) businesses were expected to see significant growth. However, please note that the landscape is dynamic, and the situation may have evolved since then. Here are some areas where AI businesses were anticipated to benefit the most in the next 24 months:
Healthcare AI:
AI applications in healthcare, such as diagnostics, personalized medicine, and drug discovery, were gaining momentum. Companies focusing on AI solutions for healthcare analytics, telemedicine, and improving patient outcomes were expected to see growth.
Finance and Fintech:
AI is widely used in the finance industry for fraud detection, risk management, algorithmic trading, and customer service. Fintech companies leveraging AI for automating processes, enhancing cybersecurity, and providing personalized financial services were likely to benefit.
Autonomous Vehicles:
Companies working on autonomous driving technology and related AI systems were expected to continue growing. This includes businesses developing AI for navigation, object recognition, and decision-making in self-driving cars.
E-commerce and Retail:
AI-driven recommendation systems, chatbots for customer support, inventory management, and demand forecasting were areas where AI was making significant contributions in the retail sector.
Cybersecurity:
AI is increasingly being used to enhance cybersecurity by detecting and preventing cyber threats. Companies specializing in AI-driven cybersecurity solutions were expected to see increased demand.
Manufacturing and Industry 4.0:
AI applications in predictive maintenance, quality control, supply chain optimization, and robotics were gaining prominence in manufacturing. Businesses focusing on AI solutions for smart factories and industrial automation were likely to benefit.
Natural Language Processing (NLP) and Conversational AI:
The demand for NLP technologies and conversational AI in chatbots, virtual assistants, and customer service applications was on the rise. Companies specializing in natural language understanding and generation were poised for growth.
Edge AI:
With the increasing need for real-time processing and decision-making, edge AI, which involves running AI algorithms locally on devices, was gaining importance. Businesses offering edge AI solutions for various applications, including IoT devices, were expected to thrive. It’s crucial to stay updated on the latest industry trends, as the AI landscape is continually evolving. Companies that can adapt to emerging technologies and address specific industry challenges are likely to gain the most benefit from AI advancements.
Good stuff, I’ll admit, and pretty well-informed. What’s missing? What’s going to keep the gold rush alive over the next two years? Will the peak hype reported today by MIT in response to Gemini’s revelations?
Peak AI Hype – MIT Review. (check out MIT’s review for yourself)
What I’m going after is this question:
What can you and your compatriots do today to harness available *ai* power tools for their workflows and predictive/generative marketing? [OH, wait, that’s my perspective.]
I want to understand how marketing, sales, and business is going to be positively enhanced by *ai* that is available now. I want to understand more about ai content, ai SEO, ai CRM, ai networking, ai writing, ai design, ai ux for ai. I want the answers. I want to accelerate my clients’ prospecting funnels. I want to turn ideas and technologies available today, into competitive gold for my clients.
I’m an explorer. I’m a catalyst.
I’m a marketer and a storyteller.
I want to win at business.
My business is helping other businesses kick ass.
Back here in the real world, I was privileged to work with a young AI-enhanced site search company called SearchUnity. We launched 10 online customer learning and support centers with the SearchUnity engine being the secret sauce. With ai models processing all the nuanced data from our incoming visitors and their quest for information we were able to answer some important questions about user goals, available content, and content gaps. The search results were tailored bot give each online visitor a search experience adapted to their needs, even if they were slightly unclear with their keywords.
The UX researcher in me was happy as our customer experience improved even before adding web personalization. The support team was happy because 25% of our customer support questions never generated a support ticket. The customers were able to answer the question themselves, with AI guiding them to more specific answers than traditional search options. This justified the budget and helped us launch more communities. Fewer support tickets means less cost to the business. (The AI enhancement paid for itself in the first 30 days of use.)
The biggest payload for the business, however, was the data insights and predictive suggestions for improvement. More than gap analysis and content aging and retirement, we were able to measure which help content was most effective in capturing and eliminating future tickets. Using the *ai* again, we were able to shape future search results to favor the most effective support content. The *ai* engine made money for the company, made happier customers, and made it easier for content marketers and tech support to build better content.
The last part of the configuration we are just starting to play with is something called “search sentiment.” Rather than just keywords (how Google and other search engines work) “sentiment” is the question beyond the keywords. Trying to predict what the visitor is actually searching for based on patterns and previous results data. They may put in +data center +chicago +esg, terms that would typically point to a Chicago data center’s ESG page. The smarter result might recognize a “data center shopper” with “ESG” requirements. The potential here is for the AI-enabled journey to be more prescriptive to the question the keywords suggested, and in turn, bias the content toward a sales journey, rather than a “virtual tour of Chicago 10” journey.
The horizon is on fire with AI enhancement engines. I’m arming myself with experts who have “done AI” in many forms. The ever-smarter chatbot is interesting. The intelligent agent is within reach. And the co-pilots are popping up in every business and app imaginable. And 2 years from now the battlefield will be littered with snazzy .ai companies already run out of juice, customers, or speculative capital.
What *ai* equation makes the most sense for your business today? What real-world precedents can your business harness for growth and profit? Find the smartest people in the *ai* room and then listen. That’s what I’m doing.
If you want to know more about our stealth professional services consultancy, contact me directly.
Today we have ai-augmented tools. We have human-augmented and trained *ai.* What’s next? Will *ai* suddenly become self-aware? Is quantum ai a thing or a sci-fi fantasy?
John McElhenney — LinkedIn
Please check out a few of my books on AMAZON.
Especially this one, about living a creative and human life of intention and joy. 100% human generated – with the exception of ai-assisted spelling.
