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When enterprises hire external firms, they outsource not just costs but also institutional knowledge. AI platforms can reverse this by capturing learnings from external engagements, building a proprietary 'brain' for the company and keeping knowledge in-house.
Sequoia partner Julian Beck advises that AI services ("autopilots") will initially target work that companies already outsource. This strategy avoids internal reorgs and firings, replaces an existing budget line cleanly, and targets buyers who are already comfortable with external work products.
The primary bottleneck for advancing AI is high-quality, tacit data—skills and local insights that are hard to digitize. Individuals can retain economic value by guarding this information and using it to train personalized AI tools that work for them, not their employers.
The key for enterprises isn't integrating general AI like ChatGPT but creating "proprietary intelligence." This involves fine-tuning smaller, custom models on their unique internal data and workflows, creating a competitive moat that off-the-shelf solutions cannot replicate.
The future consulting model may flip traditional roles. Instead of hiring firms for primary analysis, organizations could develop their own 'agentic AI' for strategy creation and use external human experts simply to validate the AI's output, relegating consultants to a secondary role.
The true enterprise value of AI lies not in consuming third-party models, but in building internal capabilities to diffuse intelligence throughout the organization. This means creating proprietary "AI factories" rather than just using external tools and admiring others' success.
Beyond individual productivity gains, AI's strategic enterprise value is its ability to re-engineer core operations. This automation creates significant efficiency savings, unlocking capital that can be reinvested into strategic technology spending without negatively impacting financial returns.
Most view AI for efficiency, but its true power lies in handling routine tasks to free up human talent. This unlocks capacity for strategic, creative, and relationship-driven work that fuels innovation and growth, shifting the question from cost savings to new capabilities.
The most significant value from AI is not in automating existing tasks, but in performing work that was previously too costly or complex for an organization to attempt. This creates entirely new capabilities, like analyzing every single purchase order for hidden patterns, thereby unlocking new enterprise value.
Unlike human employees who take expertise with them when they leave, a well-trained 'digital worker' retains institutional knowledge indefinitely. This creates a stable, ever-growing 'brain' for the company, protecting against knowledge gaps caused by employee turnover and simplifying future onboarding.
The ultimate value of AI will be its ability to act as a long-term corporate memory. By feeding it historical data—ICPs, past experiments, key decisions, and customer feedback—companies can create a queryable "brain" that dramatically accelerates onboarding and institutional knowledge transfer.