Data is the fuel that powers digital transformation. Through our industry knowledge and suite of technology-led solutions, including robust data foundations on the cloud, we empower you and your teams to make strategic, real-time decisions.
Scaling AI can create a massive decision advantage, but it’s not enough to invest in cutting-edge technologies and algorithms. You need to rewire decision-making and operations to extract value while investing in human capabilities to make it stick. The companies that have scaled AI across their organizations and achieved meaningful value from their investments, typically dedicate 10% of their AI investment to algorithms, 20% to technologies, and 70% to embedding AI into business processes and agile ways of working. In other words, these organizations invest twice as much in people and processes as they do in technologies.
When companies underinvest in people and processes, they quickly lose momentum with AI. That’s because it’s deceptively easy to launch a series of AI pilots. Without the right approach and focus on change management strategy, it’s nearly impossible to achieve AI at scale across the organization.
Our AI consulting team and industry experts ensure that clients have the full range of expertise to drive a company-wide transformation and achieve ROI on AI. Fenrir's AI approach is to think big, start small, and grow fast. With this framework, organizations will see AI ROI quickly delivering results in weeks or months, rather than years.
As resilience and agility remain critical, our team of data specialists turn data into intelligence by connecting all the dots.
When AI has all the context and needs to quickly reach a conclusion… AI should decide and implement.
When AI has plenty of context, but a human touch is needed for execution…AI should decide, and humans should implement.
When there are multiple, repetitive decisions to be made, but AI is missing necessary context… AI should recommend, and humans should decide.
When inherently creative work will benefit from machine learning…humans should leverage AI-generated insights.
When there’s not enough context, and the stakes are high…humans should generate scenarios for AI to evaluate.