Key AI Milestones Leading to 2025

2018 – BERT: Contextual Language Understanding

Google’s BERT model introduced deep bidirectional language comprehension, allowing AI to understand words in context rather than in isolation. This breakthrough laid the foundation for “reasoning” in NLP systems. In compliance, BERT’s contextual understanding meant that tools could more accurately interpret documents and communications, improving tasks like adverse media screening and entity resolution. By capturing nuance (e.g. distinguishing a client name in context), BERT set the stage for AI to identify suspicious patterns with far fewer false alarms.

2020 – GPT-3 and Generative AI

OpenAI’s GPT-3 marked a tipping point for AI in 2020. As a 175-billion-parameter model, GPT-3 demonstrated astonishing ability to generate human-like text, popularising large-scale generative AI. Its public API sparked early enterprise interest in applying AI to diverse tasks — from drafting reports to analysing unstructured data. For banks, GPT-3 proved that one model could handle a broad range of compliance tasks (e.g. drafting SAR narratives or scanning transaction descriptions), hinting at huge efficiency gains. This milestone showed financial institutions that AI could generate insights and narratives, not just classify them, auguring new ways to automate compliance workflows.

2022 – ChatGPT Brings AI Mainstream

The launch of ChatGPT in late 2022 propelled AI into the mainstream, both public and corporate. Within two months of release, ChatGPT reached 100 million users — the fastest adoption of any app in history — igniting a “frenzied” use of generative AI in daily work. For compliance teams, ChatGPT’s success normalised AI-driven assistants for tasks like employee training, policy questions, and customer interaction. Banks began piloting conversational AI for customer due diligence Q&A and internal knowledge management, as ChatGPT proved even non-experts could comfortably engage with AI. This watershed moment greatly accelerated management buy-in for AI solutions across risk and compliance functions.

2023 – Silent Eight Milestone: Global Compliance AI Deployment 

In 2023, AI made a decisive leap from concept to practice in financial crime compliance. Silent Eight deployed its AI-driven Name Screening Adjudication system across all business lines of a major global bank (Standard Chartered) in 40+ markets. This was a landmark: a reasoning-capable AI, operating at scale to automatically resolve sanctions, PEP, and adverse media alerts. Crucially, the system provides explanations for each decision, allowing investigators and regulators to understand its logic. In fact, Silent Eight’s platform became one of the first to earn regulatory approval for auto-closing alerts, thanks to its transparent and explainable output. This real-world success showed that trusted AI can dramatically reduce false positives and manual workload while satisfying regulators – a catalyst for more “agentic” AI and knowledge automation in compliance.

2024 – EU AI Act and Explainable AI

Regulation caught up with innovation in 2024 when the EU AI Act was approved – the world’s first comprehensive framework for AI. This legislation set a global precedent, imposing strict requirements on high-risk AI (including many financial services applications) and elevating governance, transparency, and accountability as top priorities. Critically, the Act emphasises explainability: AI systems must be able to explain their decisions to ensure they are fair and compliant. For banks, the EU AI Act cemented the importance of explainable AI in areas like fraud monitoring and credit risk models. It gave compliance teams a clear mandate to use AI that is not a “black box” but rather auditable and aligned with ethical and legal standards. This regulatory milestone reinforced that effective AI adoption in finance goes hand-in-hand with robust oversight and trust.

2025 – Reasoning AI in Production

By 2025, advanced reasoning-capable AI had entered full-scale production in many enterprises. Banks and insurers began deploying large language models fine-tuned for domain-specific reasoning, enabling complex decision support in day-to-day operations. For example, Morgan Stanley integrated OpenAI’s GPT-4 into its wealth management workflow, with over 98% of its advisor teams using an AI assistant to instantly retrieve research insights and answers. These new systems can analyse vast quantities of structured and unstructured data, then draw conclusions or recommendations in a way that mimics human analytical reasoning. Importantly, they do so with guardrails: companies evaluate and tune these models to ensure outputs are accurate, consistent, and explainable. The result is that regulated industries can leverage AI for sophisticated problem-solving (from transaction anomaly analysis to automated audit reports) while maintaining the high standards of accuracy and accountability that regulators expect.

Trusted AI: Operational Gains and Regulatory Readiness

Together, these milestones have paved the way for global banks to deploy AI that is both highly effective and regulator-ready. Explainable AI techniques now allow models to provide clear justifications for their alerts and decisions, addressing regulators’ demands for transparency while dramatically speeding up compliance work. Institutions are realising major operational benefits – AI-driven automation is cutting costs and processing times, with some reporting a 20-40% reduction in compliance operating costs thanks to efficiency gains. At the same time, banks are better prepared for regulatory scrutiny: AI systems can be audited, controlled, and quickly adjusted to new rules (as exemplified by the EU AI Act’s requirements). In essence, by 2025 the financial industry has entered the dawn of mainstream, trusted AI – scalable solutions that not only enhance prevention of financial crime, but do so in a way that meets the stringent standards of global regulators. The result is a new equilibrium where innovation and compliance strengthen each other, empowering banks to combat risks with greater speed and confidence than ever before.