The 21st century has brought many incredible new technologies that were once dreamed about in old sci-fi epics, and even some technologies we never saw coming. However, artificial intelligence — sometimes called machine intelligence or just AI — is proving to be one of the most disruptive of all. It’s already being applied by businesses across the globe in a variety of ways, from automating a portion of customer communications to determining product/market fit.

A survey of CEOs from small and medium-sized businesses conducted by executive coaching company Vistage found that AI is quickly becoming an important part of business processes. In the survey, 29.5% of leaders said that of new technologies, AI will have the greatest impact on their business in the next year.

But you don’t have to look to the future to see what AI may be able to do for your business now. Tools have been developed for virtually every task, with AI-based tools offering several benefits including:

• Reducing time spent on tasks

• Lowering costs

• Increasing results

• Improving flexibility and responsiveness

• Reducing risk

In the finance industry, some lenders have started using (and my company has begun testing) machine learning/AI to improve the risk assessment process.

Whether you’ve already begun using AI technology to grow your business or not, you may not be aware of all the benefits artificial intelligence offers. Here are four ways artificial intelligence can help your small business.

1. Improve Sales And Marketing With An AI-Infused CRM

Customer-relationship management (CRM) systems are designed to gather customer data across communication channels such as email, phone and social with the purpose of helping improve and even automate the sales process. Platforms such as Salesforce have begun implementing AI that helps small business owners analyze customer feedback from those communication channels and then automatically adjust marketing and lead generation activities based on that information.

AI-infused CRMs can not only maximize lead generation results, allowing you to generate more leads for an equivalent amount of marketing dollars, but they’ve begun to show how AI can be used to acquire marketing- and sales-relevant insights, optimizing nearly the entire customer acquisition process.

2. Automate Customer Communications (With A Chatbot)

Both product- and service-based small businesses have begun using chatbots on their websites to initiate customer communication and help answer questions. Think of it as a sales and customer service rep that works for you 24/7, even when you sleep.

Chatbots are likely something you’ve already encountered before, whether you realized you were dealing with AI or not. If you’ve seen one of those popups on the bottom right of the screen when you first visit a website asking if you have any questions, you’ve encountered a chatbot.

Many small businesses don’t have dedicated customer service or sales teams yet. If that’s you, chatbot AI can help alleviate the pressure and allow you to focus your time on the tasks that matter most.

3. Streamline Human Resource Tasks

One of the more unexpected areas AI has begun to creep into is human resources. AI tools have been developed that not only help streamline the hiring and onboarding process but also acquire feedback from new employees about how HR can improve those processes, both of which can have a real impact on a company’s bottom line.

AI can be used to automatically wade through hundreds of applicants to find those that most closely match the criteria you’re looking for, not only increasing the likelihood that you find the best candidate available but saving you valuable time and resources. Plus, once the candidate is brought on board, software can serve as a knowledge base for employees with questions on things such as benefits and company policy.

This not only helps reduce the time spent during the hiring process; it can also increase the number of quality applicants you receive (because you otherwise wouldn’t have been able to wade through hundreds of applications) and save HR time on the back end by cutting down on answering new employee questions.

4. Acquire Competitive Intelligence

Ever wish you had a way of analyzing every bit of digital information your competitors produce — from written and video content to social media posts — quickly and easily? AI can do that. Several tools have been created that allow you to keep tabs on everything your competitors do online, gather the data and then distill it into easy-to-read reports. Competitor analysis tool Crayon, for example, uses AI to track competitors across various digital channels such as their websites and social media and gathers a variety of data, such as slight adjustments in their marketing language and pricing changes.

These types of AI competitive intelligence tools let you gather much more detailed information faster, allowing you to respond faster and more efficiently to changes in your industry that could affect your business.

AI has only begun to enter the workplace. However, it already shows great promise as a valuable tool that can not only save you time and money but improve nearly every facet of your daily processes.

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There are many qualities that we search for in great leaders: wisdom; loyalty; constancy; courage; the ability to communicate persuasively, balanced with a willingness to hear uncomfortable truths and to change direction. But when it comes to a great data leader, a crucial role in an increasingly digitalised era, the defining characteristics vary slightly. Let’s explore what they are:

Ability to embrace change

To work in Information Technology in the early 21st century is to live in an era of unprecedented – and accelerating – change. New technologies are proliferating at such speed that even domain experts are struggling to keep up with new logos that appear in presentations summarising recent arrivals.

Furthermore, more data than ever before is available to support analysis, and in greater variety. Established methods for functions such as software development, information management and governance and the design and development of architecture and infrastructure are cracking under the twin pressures of the “new” and the requirement to do more, more quickly, with the same or fewer resources. It’s clear that these are challenging, but also exciting times for data leaders.

Little over two decades ago, the industry regarded business processes as ever-changing, but data structures as largely constant and stable. Businesses believed that if they modelled their data correctly and exhaustively, they would be largely insulated from changes in the world around them.

But in an era when the big web properties can make thousands of changes to their web-sites every month, the idea that we should map each-and-every new attribute to a well-defined and fixed domain in half-a-dozen downstream target systems now appear quaint and other-worldly.

“Big Data” is sometimes represented as a veritable Tsunami: the reality is that the challenge for today’s data leaders is not in dealing with a single, giant wave of data – but rather in working out how to manage and exploit scores of rivers of data, each of variable structure, quality, provenance, reliability and value.

Adaptability is key

In his seminal essay on software development, Fred Brooks observed many moons ago that it is the termites that technology managers and leaders should worry about, not the tornadoes.

For today’s data leader, the volume of data – the tornado – is far less of an issue than the variety, and the complexity that comes with managing that variety.

Without an adaptable leader at the helm, it’s impossible for organisations to succeed merely in managing that change, never mind exploiting it to drive business value. DevOps, Agile development methodologies, schema-less information management strategies, user-centred models of data governance, cloud and as-a-service deployment options, Deep Learning – all of these are merely tools that make more-or-less sense in different circumstances and for different use-cases.

Recognising and celebrating the plethora of new technologies, tools and frameworks now available to us – and adapting to circumstance by making appropriate choices in different scenarios – is the hallmark of success for today’s data leaders.

Einstein might have been thinking of the 21st century data-driven business when he observed that “everything should be made as simple as possible, but no simpler”.

Today’s adaptable data leader can make smart choices about when and where to avoid over-simplification to avoid leaving business value on the table – and where to enforce simplification, to avoid the unnecessary complexity that slows business to a crawl. Because to adapt is first to make intelligent choices about what is merely important – and what is vital.

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