
From Model Governance to Machine Agency: Governing AI that Acts, Not Just Answers
Learn how to govern Agentic AI with human oversight, delegated authority, runtime controls, and accountability to enable secure, responsible enterprise AI.
Current economic conditions consisting of a labor shortage and high inflation, which is accelerating costs, require that companies focus on productivity and automation when investing in Digital Business. In 2021, overall investment grew 7.4%, and for technology, this rate was 14%. In 2022, it will increase anywhere from 7.7% to 10.3%, and the majority of these investments will be in CPG/retail, manufacturing (supply chain is a key area of focus), and the services industry. These investments are geared towards increasing productivity and improving the bottom line.

Examples of investments to improve productivity include Chipotle’s focus on automating repetitive tasks and Walmart’s emphasis on warehouse automation. In the automotive industry a key focus is on leveraging vehicle data that can be monetized to generate new value creation beyond vehicle manufacturing. Recently financial and professional service companies experienced a rise in productivity by creating a flexible working environment through remote work options. According to the Labor Department this has led to at least a one percent improvement in productivity.
What investments should companies make that drives sustainable growth and organizational agility to create value? The answer is Digital Business. Achieving digital maturity is also about simplification and automation to create an agile engineering culture enabling speed and scale. As companies ramp up their investments it is imperative that they focus on quickly delivering value and outcomes.
Investing in this approach enables flexible work environment leveraging global resources, gig workers, leading to simplification and automation. Most important among these is the ability to simplify any business function to create effective end-to-end workflows for collaboration. Data is brought together from various sources, is analyzed with an agile approach to create a single source of truth (SSOT). This can be applied to any business function leading to better decision making and transparency. In addition, applying appropriate algorithms like AI/ML to the SSOT will produce more effective predictive tools and facilitate innovation with speed in a cost-effective way. Digital Business on its own will create unlimited opportunities and business models for growth with speed.
An MIT Technology Review article, The coming productivity boom, cited three reasons why productivity gains are expected to be bigger and faster than in the past. AI/ML, lower data storage costs, more powerful computing power, and cloud computing are driving the expected jump in productivity. Technology alone can’t achieve this; it must be done by creating a culture that fosters end-to-end collaboration between the business and technology. This is the pathway to enable growth through a SSOT and simplification to bring about a higher level of productivity and outcomes.
Digital Business is the solution to achieve effective business outcomes with speed without disrupting the current business. This is accomplished by taking an incremental approach based on priority areas to deliver outcomes on key objectives. Bringing business and technology together to collaborate creates an end-to-end perspective that brings speed leading to new and innovative solutions. That translates to higher productivity levels and value creation in the coming years.

Learn how to govern Agentic AI with human oversight, delegated authority, runtime controls, and accountability to enable secure, responsible enterprise AI.

Swift’s SR 2026 delay changes the ISO 20022 roadmap. Learn what banks need to do now on structured addresses, compliance, data quality and migration.

Code generation got fast. Getting an autonomous workflow into a bank’s production control environment did not. In Banking & Financial Services (BFS), the blocker is rarely the model; it’s trust. A risk officer will not sign off on a system that cannot say why it flagged something, that does its arithmetic inside a language model, or that leaves no audit trail an examiner can open. That is exactly the gap most agentic pilots die in.
Over the last two quarters, we built a portfolio of ten BFS agentic offerings on Alti AIOS™, Altimetrik’s AI Operating System, and deployed them on two stacks: Google Cloud with Gemini and AWS with OpenAI. This piece is the architecture and design principle behind them.
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