Akkio will present at the Santa Cruz Works New Tech on September 1, 2021. Be sure to get your tickets now!

AI has become a hot topic over the last few years—once reserved for science fiction movies and high-tech experiments in specialized firms, artificial intelligence has finally begun to enter every aspect of our lives. 

Take Google, which uses AI to rank content and show information based on your search history and interests—in addition to powering Google Ads, Google Maps, and a whole suite of other products with AI.

AI strengthens the work of machines while amplifying human intelligence—it’s what makes digital assistants like Siri or Alexa so helpful, enabling people to automate menial tasks and have better experiences with digital products and services.

The Challenges With Traditional AI

Implementing AI used to require extensive technical resources, creating a chasm between technical and non-technical teams. Additionally, this meant that entire small-and-medium businesses couldn’t implement AI.

Traditional AI requires a plethora of technical skills — both for building an algorithm as well as for keeping it up-to-date with data changes. In addition, deploying machine learning models requires adequate server infrastructure: large amounts of compute cycles, ample storage space, fast networks, and so on. These requirements mean that just about any SME will have a hard time getting started with AI.

On top of that, you’ll need sufficient funds to cover the costs associated with running machine learning models: in terms of hardware, software licenses, expertise in the field, and so on. Once you’ve got all those pieces together, then comes the hard part: setting up a pipeline from your data acquisition system to your ML model, training the model, generating predictions or insights, evaluating them against reality, and finally scaling up deployment if appropriate. 

In addition, many businesses aren't tech-savvy enough to be able to set up pipelines from one system into another — whether it’s merging data from multiple systems or even deploying AI into specific software, from Salesforce to Snowflake.

Overcoming The Challenges in AI

We’ve come a long way since the days of expert coders, expensive servers, and mind-numbing math. Today, you don’t need to be an elite programmer or have a large IT department to use AI algorithms and gain a competitive advantage in your industry. 

No-code AI tools like Akkio democratize access to machine learning technologies—allowing even non-technical users to build and deploy models. You no longer need top-tier hardware or software, specialized data scientists or engineers—or any technical expertise at all.

As a result, no-code AI is now being used by non-technical teams in businesses big and small, across marketing, sales, finance, HR, and more.

AI enables marketers to use data to identify the best time to launch a campaign, as well as which channels will generate the most revenue. AI is also being used to improve lead scoring in CRM systems, by identifying patterns that indicate high-value potential customers.

Using machine learning in sales can help a company increase conversions by predicting which leads are likely to convert. It also helps companies reduce the amount of time it takes to close any given deal, which makes profits higher.

In finance, no-code AI can be used to predict credit risk. For example, the use of deep learning allows startups to develop models that can accurately predict whether a given loan applicant will default on their loan payments. Similarly, machine learning is used in fraud detection and prevention.

Finally, even HR has begun exploring the benefits of AI—with good reason: it helps automate processes and streamlines operations. For example, a machine learning model can be built to predict the likelihood of an employee leaving the company. This model can be used to inform decisions regarding the retention of employees, such as offering performance-based incentives or stress-testing vacation policies. 

Ultimately, no-code AI is bridging the chasm between the technical and non-technical, allowing people without advanced computer skills to begin experimenting with AI. It's also enabling SMEs to compete with massive firms and access AI without building the infrastructure themselves. And YES, we are HIRING.