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DTSTART;TZID=America/Chicago:20260917T190000
DTEND;TZID=America/Chicago:20260917T200000
DESCRIPTION:Name: Venkata Phani Patelkhana(Independent Researcher | IEEE Se
 nior Member)\n\nTopic: Agentic AI in Energy Operations: Where Traditional 
 Systems Meet Autonomous Intelligence\n\nAbstract:\n\nAI is becoming import
 ant across many industries\, including energy. It can support areas such a
 s equipment monitoring\, maintenance planning\, forecasting\, incident inv
 estigation\, field operations\, and operational decision support.\n\nAgent
 ic AI goes beyond providing answers. An AI agent can understand a goal\, c
 reate a plan\, select approved tools\, and perform multiple actions. This 
 additional autonomy also introduces new security and governance concerns. 
 A valid user identity does not automatically authorize every agent\, skill
 \, tool\, or downstream action.\n\nThis session examines these challenges 
 from an enterprise AI architecture and security perspective. It introduces
  the concept of an Agent Control Layer for managing identity\, context\, p
 ermissions\, runtime authorization\, human approvals\, observability\, and
  audit.\n\nThe session also references the published research “Zero-Trus
 t Gateway Protocol for Multi-Tenant AI Agents” as a potential implementa
 tion pattern for applying least privilege\, per-request verification\, ten
 ant isolation\, and skill-level access control to AI-agent interactions.\n
 \nUsing an energy control-room analogy\, the session explains a simple ide
 a: a valid badge may allow someone to enter\, but it does not authorize ev
 ery switch. In the same way\, an authenticated AI agent should not receive
  unlimited authority.\n\n"The smarter and more autonomous an AI agent beco
 mes\, the more carefully its access and actions must be governed."\n\nSpea
 ker(s): Venkata Phani Patelkhana\, \n\nHouston\, Texas\, United States
LOCATION:Houston\, Texas\, United States
ORGANIZER:megha.ee21@gmail.com
SEQUENCE:2
SUMMARY:Topic: Agentic AI in Energy Operations: Where Traditional Systems M
 eet Autonomous Intelligence
URL;VALUE=URI:https://events.vtools.ieee.org/m/569350
X-ALT-DESC:Description: <br /><div><strong>Name</strong>:&nbsp\;<strong>Ven
 kata Phani Patelkhana(</strong>Independent Researcher | IEEE Senior Member
 )</div>\n<p>&nbsp\;</p>\n<div>&nbsp\;</div>\n<div><strong>Topic</strong>:&
 nbsp\;Agentic AI in Energy Operations: Where Traditional Systems Meet Auto
 nomous Intelligence</div>\n<div>&nbsp\;</div>\n<div><strong>Abstract:&nbsp
 \;</strong></div>\n<div>\n<p>AI is becoming important across many industri
 es\, including energy. It can support areas such as equipment monitoring\,
  maintenance planning\, forecasting\, incident investigation\, field opera
 tions\, and operational decision support.</p>\n<p>Agentic AI goes beyond p
 roviding answers. An AI agent can understand a goal\, create a plan\, sele
 ct approved tools\, and perform multiple actions. This additional autonomy
  also introduces new security and governance concerns. A valid user identi
 ty does not automatically authorize every agent\, skill\, tool\, or downst
 ream action.</p>\n<p>This session examines these challenges from an enterp
 rise AI architecture and security perspective. It introduces the concept o
 f an&nbsp\;<strong>Agent Control Layer</strong>&nbsp\;for managing identit
 y\, context\, permissions\, runtime authorization\, human approvals\, obse
 rvability\, and audit.</p>\n<p>The session also references the published r
 esearch&nbsp\;<strong>&ldquo\;Zero-Trust Gateway Protocol for Multi-Tenant
  AI Agents&rdquo\;</strong>&nbsp\;as a potential implementation pattern fo
 r applying least privilege\, per-request verification\, tenant isolation\,
  and skill-level access control to AI-agent interactions.</p>\n<p>Using an
  energy control-room analogy\, the session explains a simple idea: a valid
  badge may allow someone to enter\, but it does not authorize every switch
 . In the same way\, an authenticated AI agent should not receive unlimited
  authority.</p>\n<blockquote>\n<p><strong>"The smarter and more autonomous
  an AI agent becomes\, the more carefully its access and actions must be g
 overned."</strong></p>\n</blockquote>\n</div>
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