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Indebta > Small Business > How AI Is Good For Modern Business Decision-Making
Small Business

How AI Is Good For Modern Business Decision-Making

News Room
Last updated: 2023/06/06 at 7:03 AM
By News Room
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Savvy business leaders have been following AI developments for years, long before ChatGPT stormed onstage in 2022. AI is well on its way to changing the work landscape; Goldman Sachs’ March 2023 prediction is that AI could replace up to 300 million full-time jobs worldwide by 2030.

Contents
1. Empowering Real Estate Investors to Make Informed Decisions2. Reducing Manual Project Management Workloads3. Synthesizing Vast Amounts of Digital Information to Drive Evidence-Based Decisions4. Uncovering Hidden Patterns and Preferences in Consumer BehaviorLeveraging the Potential of AI in Business

That’s a legitimately frightening headline for professional services workers already insecure about their economic worth. Fortunately, the details are more encouraging. Goldman Sachs predicts a new wave of technological innovation and a 7% increase in the total value of goods and services produced worldwide. In other words, a productivity boom. One driven by AI’s rapidly improving ability to inform and shape business decisions.

It’s already happening, too. Here’s how AI factors into modern business decision-making in four key areas.

1. Empowering Real Estate Investors to Make Informed Decisions

Most independent real estate investors know that the best deals fly under the radar: short sales, foreclosures, and especially unlisted properties.

Comprehensive valuation and lead-generation tools like DealMachine are showcasing the power of AI in real estate. Tools like this go beyond the MLS properties everyone else is chasing to uncover hidden opportunities. They have proprietary valuation models that help investors determine whether an opportunity actually pencils out.

AI-powered real estate tools can’t (yet) prevent investors from making the wrong decision. But by providing much more information and capability than non-AI predecessors, they take much of the guesswork and grunt work out of the process.

2. Reducing Manual Project Management Workloads

Project management solutions like Airtable and Monday.com already utilize AI and machine learning to drive workflow efficiency. Continued progress in this space will likely be iterative, with future versions automating more and more of the time-consuming legwork.

But it’ll be dramatic nonetheless. Back in 2019, Gartner predicted that AI could automate 80% of project management tasks by 2030. Today, that seems like a conservative estimate. Humans will need to be involved for the foreseeable future, but individual project managers will be able to do much more than before. They’ll make far fewer of the small business decisions inherent in the project management workflow and focus on the big, strategic ones instead.

3. Synthesizing Vast Amounts of Digital Information to Drive Evidence-Based Decisions

Search engine technology has dramatically improved in the past 20 years, but the basic model hasn’t. You type in a query, the algorithm tries to understand what you mean, and then it spits out a bunch of links that it thinks are relevant.

Often, the results are outstanding. And often, they’re not. Iterative improvements have worked well enough until now, but it’s clear that the model has fundamental flaws.

AI could change that, perhaps sooner than we think. Google’s new Search Generative Experience (SGE) offers a glimpse at a future where AI responds to your query and analyzes the vast amount of information in that response. In human terms, it clicks the links and summarizes their content without any action on your part.

It’s easy to see how SGE could streamline business decision-making and help executives and their direct reports synthesize information much more quickly. While it won’t become Google’s default search model tomorrow, it’s coming, and the implications could be profound.

4. Uncovering Hidden Patterns and Preferences in Consumer Behavior

AI chatbots have been a customer service staple for years now. Machine learning algorithms have steadily expanded their influence in digital marketing as well.

The next frontier is AI-driven behavioral analysis and predictive marketing. That is, figuring out what the customer wants before they know it themselves. You could argue that talented human marketers already do this, and you’d be correct. However, humans don’t work as quickly as algorithms and often miss opportunities hiding in plain sight.

Like other applications for AI in business decision-making, predictive marketing’s value lies in freeing up humans to focus on strategic tasks that (for now) they can still do better than algorithms. People can direct campaigns and make connections at a high level, while automation takes care of the rest.

Leveraging the Potential of AI in Business

AI tech is already indispensable for business decision-makers in industries as diverse as real estate, human resources, and healthcare. And its ability to support and improve human decision-making is advancing fast. Wherever you work and whatever your role now is the time to get comfortable leveraging its potential. Because while AI might not replace your job anytime soon, it could advance your career.

Read the full article here

News Room June 6, 2023 June 6, 2023
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