Chief AI Officer
Jason is the Founder and Managing Director of SalesFix, a Salesforce consulting partner specialising in digital transformation and customer engagement. With more than 20 years of experience spanning management accounting, business leadership and technology consulting, he has helped organisations connect customers, partners and employees through streamlined business processes powered by Salesforce. A passionate advocate for innovation and strong organisational culture, Jason believes successful transformation is built on the combination of people, process and technology. Under his leadership, SalesFix has developed a reputation for delivering practical, outcome-focused Salesforce solutions that create long-term value, visibility and sustainable business growth.
AI is Easy. Readiness Is Hard - How organisations move from AI curiosity to trusted adoption. Getting access to AI is easy. Building an organisation that can trust it, govern it and actually use it well is much harder. In this co-presented session, Hanzel Nillo and Jason Lawrence explore both sides of AI readiness: the foundations organisations need before they scale AI, and what happens when those principles meet the reality of an actual rollout. Drawing on lessons from hundreds of data, CRM, AI and transformation programs, Hanzel will unpack the role trusted data, clear ownership, organisational alignment and practical governance play in moving beyond AI pilots and experimentation to sustainable business value. Jason then puts those principles to the test, sharing a candid account of rolling out Claude across the SalesFix team. He'll share what worked, what didn't, and what they would do differently, covering training requirements that slowed adoption, an AI policy already on its third iteration, documentation challenges and a leadership transition that tested the approach. Attendees will leave with a practical framework for assessing AI readiness, real-world lessons from an AI rollout, and the questions every organisation should be asking before moving from AI experimentation to adoption at scale.
