01
Tool use
AI helps an individual complete an existing task faster: draft, summarise, analyse, prepare, search or create.
Question: are we simply accelerating the old process?
DataLgorithmics · TechTok 2026 conference companion
The future of work is not a prompt. It is a redesign.
Use AI to improve the task, redesign the workflow and, where it creates real value, rethink the business model — while keeping trust, human judgement and measurable outcomes at the centre.
Tool useWorkflow redesignBusiness-model redesignHuman oversightContinuous learning
Three levels of AI value
Where is your organisation operating today?
The bigger opportunity usually sits beyond isolated tool use. Mature adoption changes how work flows through the organisation and what the organisation can deliver.
02
Workflow redesign
AI becomes part of an end-to-end process with permissions, data, handoffs, exceptions, controls and human review.
Question: what should humans and machines each own?
03
Business-model redesign
New services, products, experiences or delivery models become possible because the cost, speed or scale equation changes.
Question: what can we now deliver that was previously impractical?
Six practical value zones
Start with a business problem, not an AI feature.
Customer experienceFaster first response, routing, knowledge support and follow-up.
SalesLead research, segmentation, qualification, proposals and account intelligence.
Internal knowledgeSearchable policy, training, procedures and approved organisational knowledge.
OperationsWorkflow automation, exception handling, monitoring and approval orchestration.
MarketingIdeation, testing, localisation, audience insight and content operations.
AnalyticsDecision support, forecasting, scenario analysis and performance monitoring.
The D5 future-ready framework
A practical operating model for Monday morning.
D1
Decompose
Break roles and workflows into tasks, decisions, handoffs, inputs and outputs.
D2
Delegate
Identify what AI can perform, assist or accelerate — and what must remain human-owned.
D3
Deepen
Strengthen the human capabilities that become more valuable as routine work changes.
D4
Design
Rebuild the workflow around humans, machines, permissions, controls and measurable outcomes.
D5
Develop
Make continuous learning, evaluation and adaptation part of the operating model.
Capability without trust does not scale
Speed needs controls.
The higher the consequence if AI is wrong, the stronger the case for human review, traceability, permissions, evidence and governance.
Privacy & data
Know which data can be used, where it is processed and what is prohibited.
Accuracy & grounding
Evaluate outputs against approved sources and real operating requirements.
Human oversight
Define escalation, approval and accountability for material decisions.
Security & permissions
Give systems the minimum access they need and log consequential actions.
Transparency
Make important AI use understandable to the people affected by it.
Continuous evaluation
Measure quality, risk, adoption and value after deployment — not just before launch.
Conference demo route
Five ways to explore DataLgorithmics in under ten minutes.
01 · Assess
AI Readiness
Score strategy, data, governance and operating maturity.
Run assessment →02 · Value
AI ROI Calculator
Model an indicative annual opportunity and payback period.
Model value →03 · Design
Agent Spec Builder
Define goals, permissions, tools, knowledge and escalation.
Design an agent →04 · Operate
Enterprise Command
See how AI, risk, customer, commercial and reliability signals connect.
Explore command →Continue after the conference
Bring one real workflow. We can start there.
Tell us the process, bottleneck, data, people involved and what a better outcome would look like. Website enquiries continue directly through WhatsApp.