Artificial intelligence is one of the hottest topics in the business world, and speculations about its potential effects abound. Professional services giant PwC claims AI could add nearly $16 trillion to the world economy by 2030. The consultancy group McKinsey predicts $13 trillion in the same time frame. Quibble over a few trillion dollars if you’d like, but the fact remains that AI is going to be an important technological advancement that businesses will need to incorporate to stay competitive. It has the potential to make a large impact in many industries, including:
- Healthcare: AI could affect every stage of the healthcare pipeline. From streamlining drug research to helping with diagnoses and making treatments more efficient in enabling the elderly to remain independent longer, AI is poised to transform this field.
- Energy: As current energy grids age, smart grids that feature advanced AI will replace them. This artificial intelligence will analyze vast amounts of sensor data to automate resource allocation decisions. The results will be higher efficiency and the ability to seamlessly integrate a more diverse set of energy generators.
- Cybersecurity: Companies wanting to keep their data safe will need to invest in AI solutions. They will help extract useful information from enormous datasets too complex for manual analysis. Furthermore, as more bad actors gain access to this technology, firms will need to effectively combat them with their own AI.
AI’s Impact On Business
The investment into AI technology is enormous. In 2019 alone, AI-based startups received $18.5 billion in venture capital. Overall investment in the sector is predicted to nearly hit $100 billion by 2023. With this kind of funding, the business world will soon feel the impact, and the business landscape could transform through:
- Higher Productivity: AI allows knowledge workers to be more productive by automating mundane tasks. For example, it’s estimated that 40% of the work salespeople do during the sales process can be automated through the use of current AI solutions.
- Higher Employee Engagement: A Gallup survey concluded 51% of workers in the United States don’t engage with their jobs. AI has novel applications for improving this through real-time analysis. For instance, a company could employ AI to analyze random email correspondence throughout the company and produce a general outlook on morale. Armed with up-to-date insights, management can address problematic issues before they fester.
- Changes In Business Finance: The financial industry is one of the sectors AI most impacts. Through applications such as data science modeling tools, automated machine learning and AI-enabled enterprise software, financial institutions make better decisions.
Trends For 2020
2020 is a big year for artificial intelligence. More companies will introduce AI solutions into standard operating procedures. A few emerging trends include:
- Language Processing: Through the use of deep learning and other advanced algorithms, AI’s ability to decipher human language is increasing. Expect chatbots to become even more popular.
- More Accurate Simulations: Real-world situations will be modeled more accurately than ever. AI will analyze massive amounts of data and provide actionable insights without having to invest in extensive real-world testing.
- Aid For Knowledge Workers: Knowledge workers will automate unproductive tasks such as filling out forms, responding to emails and deciphering key data points.
The Big Picture
The AI revolution is already underway, and its effects will be far-reaching. If your company isn’t prepared, it will lag behind competitors that are implementing AI solutions. Here are a few tips to help you get started:
- Use Clean Data: The performance of any AI solution is contingent upon the quality of the data that’s used to train it. Use clean data that is accurate, complete, relevant and/or properly formatted — and be sure to have a clear business goal in mind so you’ll design a more effective model.
- Take A Proactive Approach To Model Maintenance: When you start building models, be sure to do so in ways that make retraining easier. No model you create and test should be considered disposable. Everything should be production-level quality.
- Replace Manual With Automated: Look across your organization, and identify any time-intensive manual process that’s a good candidate for automation. Then match that process with an AI solution that’s easy to implement and maintain.
Find interesting ways, like those above, to incorporate this disruptive technology into business practices, and you will enjoy the corresponding improvements to productivity and decision-making.