How to Introduce AI into Your Business Strategy

It’s no secret that Artificial Intelligence has moved out of the lab and into the boardroom. 64% of senior decision makers believe their organization’s future growth is dependent on AI technologies. 76% report that AI is a fundamental part of their corporate strategy. As IBM CFO Martin Schroeter says, “The debate about whether artificial intelligence is real is over, and we're getting to work to solve real business problems.” Solving “real business problems” starts with figuring out how to work Artificial Intelligence into an enterprise’s business strategy. Executives who’ve heard that AI can help grow their business often struggle with where to start. It’s one thing to read an exciting article about AI online and another to leverage that technology into a competitive advantage. For those looking to make a case for AI integration, the first step is identifying the issues the company is experiencing (declining customer satisfaction, workplace inefficiency, stagnating growth, etc.). From there you can explore how AI would address those problems to realize a return, either in profit or expanded capabilities.

What solutions can AI offer your company?

To get the most out of the Artificial Intelligence movement, it’s critical to outline how it will be used in your particular organization. AI isn’t a broad-use tool; it works best when applied to a specific problem. At its current stage of maturity, these are the most practical applications of Artificial Intelligence.

Automating repetitive tasks

There’s a lot of minutia that goes along with business. Employees spend up to 15 hours a week on administrative tasks like updating tracking spreadsheets, sending follow-up emails, and sorting leads. It reduces employee satisfaction while wasting high-value labor on low-skill tasks. Automation is an area where AI really shines. Andrew Ng, Chief Scientist of Chinese-American web services giant Baidu, created the “one second rule”: if a typical human can do a task with less than one second of thought (meaning the thought needed to determine whether action is necessary, not the time needed to complete the action), AI can automate it faster and more accurately. In case that sounds underwhelming, here’s a sample of tasks an AI can do with that second using machine learning techniques:
  • Sort an incoming business lead into the proper category
  • Post to a social media network
  • Decide if a forum comment violates community guidelines
  • Check whether a form has been filled in correctly
  • Identify a strange behavior or pattern (such as suspicious purchase activity)
  • Update a spreadsheet
Nine out of ten employees agree that automating these repetitive tasks would make them more productive. By reducing time spent on necessary but tedious tasks, automation also increases employee satisfaction and (by extension) retention.

Improving the customer experience

The internet has changed how consumers interact with enterprise. People prefer to conduct their business online whenever possible, citing convenience as their primary motivation. Gartner predicts that by 2020 consumers will manage as much as 85% of their enterprise interactions without speaking to a human. The same report reveals that 89% of businesses will compete based mainly on customer experience within the next few years. Automated natural language-based interfaces- called “Intelligent Assistants” when used in enterprise- are fast becoming the standard in all-hours customer care. IAs can handle most basic online services a customer might need. They suggest products based on current and past activity, help customers navigate a quote process, schedule appointments, or even detect whether a customer’s problem can more easily be solved by a human representative and transfer the chat. As a result, customers finish their business faster when using an IA than previous limited systems. They’re also more likely to make impulse purchases or upgrades since the suggestions are tailored to them. 70% of consumers will pay more for a hassle-free experience, so if they have a good experience through the IA they’re likely to stay even when prices trend higher. The superior experience offered by modern IAs is wearing away at old prejudices against “talking to robots” caused by awkward rule-based historical interfaces. Dan Miller of Opus Research estimates that continued positive customer experiences will completely eradicate that bias, saying “Within three years, enterprise Intelligent Assistants will be the primary point of contact to support real world commerce in the digital realm.”

Generating Timely Business Insights

Predictive analytics are among the most useful AI tools available. Once the sole domain of data scientists, analytics are now often embedded in other software to provide an extra layer of functionality. Information about marketing campaigns, equipment function, social media activity, and more can be analyzed in real time and presented in a format accessible to the non-technically inclined. Accessibility is a huge step forward for analytics, considering that the old model involved waiting for a specialist to translate data into usable graphs. Two years ago only 51% of decision makers felt they could interpret their enterprise analytics without assistance. In 2017 that number is 66% and rising. Having analytics that executives can read themselves boosts flexibility and allows for faster reactions to industry changes.

Concerns about incorporating AI into business strategy

How practical is AI for enterprise right now?

Some applications of Artificial Intelligence are more mature than others, but the above are all comfortably enterprise-ready. In fact, predictive analytics and automation are almost necessary for companies looking to grow quickly.

Will AI replace human workers?

There’s a lot of controversy over whether Artificial Intelligence will lead to a massive rise in unemployment, but that doesn’t seem to be where enterprise is trending. The majority of employers are more interested in AI for efficiency than payroll-reduction. 80% of early AI adopters say they plan to retrain or reassign staff replaced by Artificial Intelligence rather than letting them go.

How much AI is “enough”?

There are a few AI applications that every modern organization should be using (i.e., predictive analytics) but otherwise this has to be answered on a case by case basis. AI should make things easier, not more complicated. If adding it creates too much complexity, consulting with a specialist can help realign your AI solutions with your organizational goals.

Are you wondering how AI can be added to your IT infrastructure? Concepta can help! 

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