ai or ia pt. ii
hey it’s dan back with more thoughts on artificial intelligence, or as I like to thing of it, intelligent assistant (ia). today, I want to dive into the agentic era. the road ahead isn’t about choosing sides. it’s not ai versus humanity, or automation against creativity.
let’s unpack what this means.
agentic era?
this is going to be all about partnership and ai amplifying what we do best. hopefully we'll be building smarter systems, solve complex problems, and achieve goals faster than ever.
being all in means embracing possibilities while staying grounded in principles like ethics, transparency, and shared responsibility. a good example of a leader in the space is salesforce’s agentforce. designed to work alongside people, it assists on focusing on what truly matters.
agentforce
agentforce is built on the salesforce platform, which combines quick setup, pre-built templates, and integrations that bring ai agents up and running in record time. what makes these agents stand out is how they already have use cases to complement human effort.
role each agent has a clear purpose, whether it’s assisting with customer service or personalized coaching for sales teams.
knowledge armed with data from salesforce’s crm, the data cloud, it's like having teammates with encyclopedic knowledge, providing accurate, relevant information on demand.
actions action-oriented, capable of triggering workflows, running processes, and taking steps autonomously, while still staying accountable to the systems and teams they support.
guardrails built-in security features, like the einstein trust layer, it ensures agents operate within ethical and legal boundaries, escalating issues to humans when necessary.
channels agents work wherever we do, from crm platforms and slack to mobile apps and websites, which makes collaboration seamless.
the role of data in the path forward
if ai is the engine driving the agentic era, data is the fuel. this is not an exaggeration. the quality, security, and governance of the data these agents rely on determine how well they perform and how effectively they can assist.
a few core principles for managing data
governance
ensures that information is accurate, consistent, and accessible to the right people at the right time. this is how we ensure that agents don’t just act but act responsibly.
security
with sensitive information at stake, ai systems must adhere to the highest security standards. encryption, access controls, and real-time monitoring help ensure that our data is safe, and by extension, our ai partnerships remain trustworthy and accurate.
lifecycle management
data’s value evolves over time, so managing its lifecycle aka creation, use, storage, and eventual deletion is crucial for compliance and operational efficiency. lifecycle management keeps data working for us, not against us.
disaster recovery
even the most advanced systems face disruptions. robust recovery options ensure we can quickly restore all data and minimize downtime, keeping agents on track and our operations resilient.
types
service agent elevate customer support by handling inquiries without relying on preprogrammed scenarios. when it runs into a challenge, they partner with human agents to resolve issues quickly and effectively.
sales/business development representative a sales teammate who works around the clock, ensuring no opportunity is ever missed. inbound and outbound sdr/bdr agents seamlessly engage with prospects to fill in the gaps. answering questions, managing objections, and scheduling meetings. by handling these essential tasks, they enable human sales reps to focus on what they do best: building strategic relationships, closing deals, and driving meaningful business growth. we will see agents reaching out and fielding meetings for people. human outreach will become scarcer and more meaningful.
sales coach this is a perfect example of ai enhancing human effort, where agents provide personalized coaching for sales teams. by using salesforce data and generative ai, they simulate real world scenarios and help reps sharpen their skills.
personal shopper acting as a digital concierge, these agents guide customers through personalized recommendations and seamless purchasing experiences, turning online shopping into a more intuitive, customer first journey.
all in on data mastery
success hinges on how well we handle the data that powers ai. we must be all in on mastering data including its governance, security, lifecycle, and resilience.
by ensuring our data is accurate, consistent, and secure, agents can collaborate effectively. this is how we create systems that aren’t just automated but aligned with our needs and values.
the path forward
we’re unlocking new levels of efficiency, creativity, and problem-solving that neither humans nor machines could achieve alone. the human brain is still the greatest computer ever conceived, and when paired with ai, the possibilities are endless.
agentforce demos this power of partnership. agents handle repetitive tasks, provide deep insights, and enhance decision making, while humans bring strategic thinking, creativity, and empathy to the table. together, we’re building smarter, more connected systems that benefit everyone.
closing thoughts: all in
the challenge ahead is to embrace ai as a partner, not a competitor. this means working toward a shared vision where ai amplifies human effort and humans guide ai toward meaningful, ethical outcomes.
the potential of this agentic era lies in how we apply these lessons across industries, from healthcare to education to manufacturing. by investing in collaboration, governance, and trust, we can ensure the path forward is brighter for everyone.
if this sparked your interest, i’d love to hear your thoughts. reach out, subscribe, or dive into the resources below to explore this exciting new frontier.
until next time, dan
extras
