Future-focused: AI startup concepts for growing agencies

Signs you should create an AI startup

The last couple of years have felt a bit like the early days of the internet: a tech gold rush of companies, new and old, vying to make the best, most successful new product using an exciting new technology. If all the AI-related headlines, products, and tech announcements coming out each day have you thinking about your own AI startup ideas, there’s no better time than the present to enter the field.

1. Rapid adoption

One unmistakable sign of the potential for success as an AI digital marketing entrepreneur is the rapid adoption of AI technologies by business across a vast array of industry sectors. What may have once seemed like an interesting development for niche, tech-focused businesses is quickly proving to be a powerful toolkit for regular small and medium-sized businesses (SMBs) of all kinds.

AI is helping SMBs streamline their operations, enhance customer experiences, make better decisions, and more, all of which driving demand for innovative, easy-to-use AI solutions. As an entrepreneur tuned into this shift, you can offer AI solutions that directly solve your clients’ problems and help them boost their bottom line.

2. Room for innovation

Since the field is still in its early stages, the space for digital marketers to craft innovative AI-powered bundles of solutions for their clients is vast. Clients are still adapting to this brave new world, discovering out how AI can make their lives easier and boost their profits. This makes space for those with creative AI startup ideas to jump in, help clients frame their problems, and offer AI-based solutions.

3. Competitive edge

Other digital marketing businesses are using AI to enhance their offerings, and as time goes on, those that don’t adapt will likely fall behind. The right AI startup idea can help you stay ahead of the curve instead of chasing it, offering clients the leading edge of solutions available today.

Things you need to know with developing an AI product

From the consumer side, AI can feel like magic. But when it comes to developing an AI product that delivers the best possible results, it’s important to know the major considerations that determine the quality of your product.

• Data quality and relevance: Your output will only be as good as your inputs, so having a vetted system for collecting high-quality data is imperative. The accuracy and representativeness of the data directly impact the performance and reliability of machine learning models.
• Data privacy: Real-world data is used to train AI models, which introduces potential ethics problems. AI entrepreneurs should ensure their product respects both user privacy and the privacy of those represented in the data used for training.
• Machine learning algorithm choice: The machine learning algorithm you build or use will depend on the problem you’re trying to solve. Factors like the complexity of the problem, the nature of the data used to train the model, and the available computation efficiency you have access to should all inform the algorithm used. If you opt for a white label AI software, take the time to research what you can expect from its algorithm.
• Model training: Once a dataset is prepared, the “machine learning” aspect of the algorithm is kicked into gear, as it adjusts its parameters to learn to identify the aspects of the data on which it’s being trained. For example, for a digital advertising model, this might be the time of day users click on an ad.
• Continuous model improvement: In AI, models aren’t just trained once. The dynamic nature of data and user interactions means continuous model training and adaptation is required. AI startups should plan to have a system in place for regular, iterative improvement and continuous development. If a model is out of date, it won't be helpful to users.

Niches that may benefit from AI products

While consumer-facing AI products may be all about image and text generation, the technology is being applied in a far wider range of applications by businesses. Let’s take a look at some major industries and niches, and the opportunities that exist for AI startups within each of these.

Healthcare

AI solutions can help healthcare providers meet the demands of an aging, diversifying population by delivering better outcomes for patients. For example, opportunities exist for AI to be used to provide personalized treatment plans, predict the development of heart disease, cancer, diabetes, and other major diseases, improve the treatment of those diseases, and  improve robotic surgery performance.

Finance

With AI, businesses in the finance space can dramatically curb problems like fraud through advanced machine learning algorithms that can detect it early. Financial platforms can also improve outcomes for their clients without having to expand their team by implementing AI-powered investment strategies and automated trading.

Retail

AI can dramatically improve cashflow for retails by improving the management of their just-in-time delivery systems. The tech can also be used on the consumer-facing side of ecommerce with sophisticated AI chatbots and personalized product recommendations, boosting customer experience and conversions.

Manufacturing

Manufacturers can implement AI solutions to better maintain their operations by accurately predicting when equipment needs to be maintained or replaced. It can also provide precise demand prediction, helping manufacturers focus on making the right SKUs at the right time. AI can even help create smarter robots that are able to adapt and learn different tasks.

Education

Education has already been transformed by the explosion of learning, and AI can continue the revolution by tailoring education, exercises, and even teaching styles to student needs. Creating adaptive learning platforms can keep students more engaged and ensure they advance at their own optimal pace.