Closing the gap between the promise of AI and its implementation
Artificial Intelligence (AI) could be the most widely misconstrued tech term ever coined. Its long-term association with science fiction has positioned as something sinister; malevolent, almost. And even when we know its real worth there’s still a reluctance amongst businesses of all sizes to adopt a set of tools that promise so much. What’s going wrong?
AI has long been hailed as a revolutionary technology, but very few enterprises have been willing or able to take full advantage of this potential. There is a fundamental gap between the promise of AI and the reality, with many businesses focusing on small-scale projects rather than the big ticket transformation it offers.
To uncover why this might be the case, we carried out a detailed analysis of the challenges faced by its business customers. The results revealed three main challenges: Data, trust and skills.
Too many companies are careless with their data. It’s often poor quality, full of errors and out of date. The task of collecting, cleaning, analysing and leveraging data in those types of scenarios looks nothing less than overwhelming. But the doubters and disbelievers are in for a shock. According to a 2020 Forrester Consulting study, organisations that adopt and scale AI are seven times more likely to be the fastest-growing businesses in their industry.
Our customer Lufthansa, for example, recognised early on that with the right data and AI strategy, it could improve customer services, empower employees and improve operational efficiency. We worked with the airline to help them build a computer platform that its data scientists could use to test AI projects before rolling them out across the company.
The next key challenge is trust. And for AI this can be a stumbling block. The idea of machine intelligence making decisions that can take precedence over human insights has the potential to be destabilising. How can companies build confidence?
First, the vendors of AI tools need to ensure that their systems deliver decisions that are explicable, comprehendible and fully traceable. There should also be a focus on privacy, safety and fairness, supported by a framework that ensures a human review of every AI decision and action. There’s a potential pitfall here, though; the introduction of involuntary human bias, which has the possibility to inadvertently influence outcomes.
That’s why we advise companies to pick an ‘ethics official’, a person responsible for overseeing the day-to-day governance of each AI implementation and for communicating its ongoing objectives.
To fully leverage that implementation requires more than confidence; businesses also need access to a range of specialist skills. Finding deep learning, natural language processing and robotic process automation specialists is a real issue but without access to these sorts of competencies companies risk not optimising the benefits AI can deliver.
The final hurdle is bringing it all together. That’s why we have developed a range of tools and approaches for AI implementation specifically designed to help even the most hesitant business bridge the AI gap. We can help lower the barriers to entry and make AI more accessible in practical, powerful and performance-enhancing ways. Think of it as a ladder, that’s intended to help businesses scale the hurdles around AI adoption.
Our ‘AI Ladder’ has just four rungs: Collect, Organise, Analyse and Infuse. Each step is designed to create a painless progression towards the deployment of a scalable, secure and transparent AI implementation.
AI is fast becoming an integral part of modern business operations. Companies that fail to understand that will lose ground to their competition: it’s already starting to happen. Perhaps it’s time to reach for the AI ladder before that gap become an unbridgeable gulf.