Artificial intelligence (AI) is shaking up the way we do business. By 2030, the global AI market will be worth over $15.7 trillion. This is in increased productivity and commercial benefits, according to PwC. AI adoption is fast becoming essential for companies to keep – or win – competitive edge. But myths and barriers abound.
Let’s start by addressing some fundamental ‘untruths’ to help you envision the best combination of people and machines.
1. Artificial intelligence (AI) will replicate human intelligence
False. The term ‘artificial’ intelligence is misleading. Replace it with ‘augmented’ or ‘enhanced’. AI is the replacement of repetitive manual and cognitive tasks by machines that are not intrinsically ‘intelligent’. The main methods behind it? Machine learning, deep learning, and natural language processing.
Today, AI delivers two main valuable functions.
- Automation of repetitive tasks. It does this by predicting outcomes on data that has been labeled by human beings.
- Enhancement of human decision-making. It does this by feeding problems to algorithms developed by humans.
So, the real focus for you as a CEO or CIO should be this:
- What is the real value of AI for your business and how can you capitalize?
- How can you make human-machine interaction intuitive and efficient across your business?
- What are the areas in which you can harness AI to improve productivity and profitability?
- Which departments, processes and employees can you reinforce with AI’s ‘super-powers’?
2. AI is an incomprehensible ‘black box’
False. The development of the technology relies on humans. AI is able to perform complex tasks. But they are based on predetermined rules and norms supplied and monitored by humans.
AI that is explainable, provable, and transparent will be critical to establishing trust in the technology.
So, a better way for CEOs and CIOs to think of artificial intelligence is as:
- A sophisticated tool that you can leverage to augment the human intelligence of your employees.
3. AI’s productivity gains will mean widespread job losses
False. This is confusing AI augmentation with automation. Gartner says that by 2020, actually Artificial Intelligence “will create more jobs than it eliminates”.
2020 will be a pivotal year in AI-related employment dynamics, according to Gartner, as AI becomes a positive job motivator.
The number of jobs affected by AI will vary by industry. In 2019, healthcare, the public sector and education will see continuously growing job demand. Manufacturing (via robotics) will be hit the hardest. PwC backs this positive projection too:
4. Integration of AI means disruption of your company’s IT infrastructure
False. You may need some changes to take full advantage of the capabilities of AI. This could include modernization of data architecture and improvement of information security. But AI does not call for radical change.
Cloud-based Artificial Intelligence platforms today can be:
- Scalable and modular
- Integrated with existing company technologies
- Accessible to B2B applications across the entire customer relationship
- Used to exploit internal and external data
- Harnessed by companies to get a lead in their market segment
- Creators of value in a fast, simple and efficient way
5. AI will mean redesigning business processes and working roles company-wide
False. Companies will seek to ‘augment’ the productivity of their workforce. They’ll use AI technologies and robotics to automate some tasks.
But, AI has a high IQ but a low EQ, or emotional intelligence. Here’s what France Stratégie’s recent report What impact artificial intelligence on the future of work? says. “AI is not an autonomous technology that can think for itself, show imagination or creativity. These skills are fundamentally social and human-specific.”
This is why AI medical imaging may help in diagnosis of tumors. But it won’t be able to handle the complexity of care of the patient.
We agree with Deloitte. “The most valuable roles are those that enable machines to pair with skilled, cross-disciplinary thinkers to innovate, create, and deliver services.”
Businesses that embrace AI will not need pure technical competency. The most needed capabilities for the future?
- Complex problem-solving
- Cognitive abilities
- Social skills
The best data scientists are ‘bilinguals’ or ‘integrative thinkers’. They are those who can make sense of data but also the nuts and bolts of business. They can also communicate what they do to their co-workers because acceptance and buy-in are multipliers to the success of AI initiatives.
A practical application of AI
At Sidetrade, we take an entirely pragmatic approach to Artificial intelligence.
We work one-on-one with B2B companies to refine and advance their customer relations. We integrate our technologies in-house to provide them with sophisticated AI and data capability.
Our mission is to make AI easily accessible to Marketing, Sales and Finance teams. In our vision, technology does not compete with the human mind; it provides us with new insights. For example, we use Natural Language Processing algorithms to help Marketing teams to boost their conversion rates by targeting more relevant prospects with a similar customer DNA (a 360-degree view based on actions and interests) to their existing customers. At the end of the customer journey, we use Machine Learning algorithms to define and personalize the best strategies, the optimum methods and most relevant timing to collect cash faster from each customer.
It’s why our data scientists come from such a broad range of disciplines. And it’s why we insist upon ‘augmented intelligence’ over ‘artificial intelligence’. And why, ‘feel the fear and do AI anyway’ is our message to CEOs.