As we enter 2021 and another iteration of the ‘New Normal’ presents itself, businesses have a real opportunity to adopt and accelerate digital transformation using analytics and AI. By being bold, brave, and proactive those forward-thinking companies will be well placed not just for the ‘New Normal’, but the ‘Next New Normal’.
According to a recent PwC study, by 2030, AI will boost global growth by $15.7tn. As we enter 2021, executives and businesses that take the lead and embrace AI to drive digital transformation could scoop the biggest share of the prize. So, against this backdrop what are the key analytics and AI trends we should be looking out for?
- Augmented intelligence (everywhere): Combining machine intelligence with human interaction enables the ability to realise augmented intelligence and turn insights into action at speed. Expect the adoption rates of AI-powered analytics to be one of the most sought-after requirements globally ...
- Trusted AI: We will see increased lawsuits, penalties, and poor consumer reaction where there is inadequate or no control over data use. A trustworthy AI framework must be adopted to ensure all AI and data is treated ethically and without bias. The Chief Data and Analytic Officer role just got even more complicated …
- Increase in cloud: The cloud was first introduced by Eric Schmidt back in 2006. Why has it taken so long to become the norm? Over recent years, multiple cloud partners have flooded the market combined with ever more diverse SaaS platforms and capability. There are still multiple benefits that the cloud has to offer as we enter an increasingly virtual world. Expect more cloud …
- The data ecosystem: As organisations continually mine insights from various sources, data has become a key differentiator. As the demand for data increases and emerging data lakes grow to meet the demand, consolidated data marketplaces will furnish datasets, but at a price ...
- Pragmatic and human-centred AI: As consumers, users, and the wider business community become increasingly suspicious of industry AI-based analytical solutions, businesses need to take on board pragmatic AI models to identify and solve specific business problems. Expect AI innovation teams to collaborate with social science, behavioural science, and decision intelligence experts. This connection between AI and customer experience will drive a cycle in which AI models and customers co-learn and adapt ...
- Enhanced machine learning operations (MLO’s): AI solution teams MUST make MLO practices an integral part of the overall AI model lifecycle to continuously monitor and grow AI models, and maintain relevance. Failure to do so will result in rapid obsolescence ...