With Anthropic reportedly launching a ~$1.5B AI-native enterprise services/consulting venture alongside Blackstone, Goldman Sachs, Hellman & Friedman etc., it feels like we may be entering a very different phase of enterprise tech consulting.

This doesn’t look like “just another AI partnership.”

It looks more like:

• model provider + capital + deployment engineers + PE distribution
• essentially a “McKinsey of AI” / Palantir-style forward deployment model
• direct embedding of Claude into enterprise workflows instead of just selling API access

As someone learning data engineering, I’m wondering what this means for:

• Big4
• Accenture
• WITCH firms
• traditional data engineering consulting

Especially because historically these firms made huge revenue from:

• cloud migrations
• ERP implementations
• data warehousing
• BI/dashboarding
• enterprise integrations
• managed services

But now if frontier labs themselves move into:

• implementation
• workflow redesign
• agent deployment
• data integration
• embedded engineers then doesn’t that compress a lot of consulting layers?

One thing Reuters mentioned was interesting:

>

So maybe the work doesn’t disappear — it changes.

My current take:

Likely impact

• Less “generic” implementation work
• Higher pressure on billable-hour consulting models
• AI-native consulting firms may grow much faster
• Clients may prefer outcome-based pricing over long transformation projects
• Data engineering shifts from pipeline-building → AI-ready infrastructure + context engineering

What traditional consulting firms probably need to do

• Build proprietary accelerators instead of just manpower scaling
• Become experts in enterprise AI orchestration/governance
• Move from dashboards → agents/workflow automation

how a fresher in de big4 look to it ????

I've recently heard that there are no jobs in analytics. The ETL monkeys, particularly, are dying and the Power BI, business intelligence, and analytics roles are no longer sustainable in the AI world. Currently I'm seeing a lot of job postings for analytics engineers who are proficient in analytics, building analytics platforms from the ground up for internal products at Sarvam AI, Apollo Global Management, M&G Global Services. All these are particularly constantly hiring for their analytics team.

So as a fresh grad who is starting into data engineering, is it better to get an analytics role as a junior engineer at any of these firms or any other firms and later can switch to core data engineering, architecture, system design, pipelining, part of things that are core to data?